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errbotio/errbot
|
66e1de8e1d7daa62be7f9ed1b2ac8832f09fa25d
|
errbot/templates/initdir/example.py
|
python
|
Example.tryme
|
(self, msg, args)
|
return "It *works*!"
|
Execute to check if Errbot responds to command.
Feel free to tweak me to experiment with Errbot.
You can find me in your init directory in the subdirectory plugins.
|
Execute to check if Errbot responds to command.
Feel free to tweak me to experiment with Errbot.
You can find me in your init directory in the subdirectory plugins.
|
[
"Execute",
"to",
"check",
"if",
"Errbot",
"responds",
"to",
"command",
".",
"Feel",
"free",
"to",
"tweak",
"me",
"to",
"experiment",
"with",
"Errbot",
".",
"You",
"can",
"find",
"me",
"in",
"your",
"init",
"directory",
"in",
"the",
"subdirectory",
"plugins",
"."
] |
def tryme(self, msg, args): # a command callable with !tryme
"""
Execute to check if Errbot responds to command.
Feel free to tweak me to experiment with Errbot.
You can find me in your init directory in the subdirectory plugins.
"""
return "It *works*!"
|
[
"def",
"tryme",
"(",
"self",
",",
"msg",
",",
"args",
")",
":",
"# a command callable with !tryme",
"return",
"\"It *works*!\""
] |
https://github.com/errbotio/errbot/blob/66e1de8e1d7daa62be7f9ed1b2ac8832f09fa25d/errbot/templates/initdir/example.py#L12-L18
|
|
bruderstein/PythonScript
|
df9f7071ddf3a079e3a301b9b53a6dc78cf1208f
|
PythonLib/full/zipfile.py
|
python
|
LZMACompressor.__init__
|
(self)
|
[] |
def __init__(self):
self._comp = None
|
[
"def",
"__init__",
"(",
"self",
")",
":",
"self",
".",
"_comp",
"=",
"None"
] |
https://github.com/bruderstein/PythonScript/blob/df9f7071ddf3a079e3a301b9b53a6dc78cf1208f/PythonLib/full/zipfile.py#L594-L595
|
||||
openedx/edx-platform
|
68dd185a0ab45862a2a61e0f803d7e03d2be71b5
|
openedx/core/djangoapps/courseware_api/views.py
|
python
|
CoursewareInformation.set_last_seen_courseware_timezone
|
(self, user)
|
The timezone in the user's account is frequently not set.
This method sets a user's recent timezone that can be used as a fallback
|
The timezone in the user's account is frequently not set.
This method sets a user's recent timezone that can be used as a fallback
|
[
"The",
"timezone",
"in",
"the",
"user",
"s",
"account",
"is",
"frequently",
"not",
"set",
".",
"This",
"method",
"sets",
"a",
"user",
"s",
"recent",
"timezone",
"that",
"can",
"be",
"used",
"as",
"a",
"fallback"
] |
def set_last_seen_courseware_timezone(self, user):
"""
The timezone in the user's account is frequently not set.
This method sets a user's recent timezone that can be used as a fallback
"""
if not user.id:
return
cache_key = 'browser_timezone_{}'.format(str(user.id))
browser_timezone = self.request.query_params.get('browser_timezone', None)
cached_value = TieredCache.get_cached_response(cache_key)
if not cached_value.is_found:
if browser_timezone:
TieredCache.set_all_tiers(cache_key, str(browser_timezone), 86400) # Refresh the cache daily
LastSeenCoursewareTimezone.objects.update_or_create(
user=user,
defaults={'last_seen_courseware_timezone': browser_timezone},
)
|
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https://github.com/openedx/edx-platform/blob/68dd185a0ab45862a2a61e0f803d7e03d2be71b5/openedx/core/djangoapps/courseware_api/views.py#L497-L514
|
||
rushter/MLAlgorithms
|
3c8e16b8de3baf131395ae57edd479e59566a7c6
|
mla/neuralnet/layers/convnet.py
|
python
|
Convolution.shape
|
(self, x_shape)
|
return x_shape[0], self.n_filters, height, width
|
[] |
def shape(self, x_shape):
height, width = convoltuion_shape(self.height, self.width, self.filter_shape, self.stride, self.padding)
return x_shape[0], self.n_filters, height, width
|
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"[",
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",",
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https://github.com/rushter/MLAlgorithms/blob/3c8e16b8de3baf131395ae57edd479e59566a7c6/mla/neuralnet/layers/convnet.py#L62-L64
|
|||
chengzhengxin/groupsoftmax-simpledet
|
3f63a00998c57fee25241cf43a2e8600893ea462
|
symbol/builder.py
|
python
|
BboxHead.get_prediction
|
(self, conv_feat, im_info, proposal)
|
return cls_score, bbox_xyxy
|
[] |
def get_prediction(self, conv_feat, im_info, proposal):
p = self.p
bbox_mean = p.regress_target.mean
bbox_std = p.regress_target.std
batch_image = p.batch_image
num_class = p.num_class
class_agnostic = p.regress_target.class_agnostic
num_reg_class = 2 if class_agnostic else num_class
cls_logit, bbox_delta = self.get_output(conv_feat)
bbox_delta = X.reshape(
bbox_delta,
shape=(batch_image, -1, 4 * num_reg_class),
name='bbox_delta_reshape'
)
bbox_xyxy = X.decode_bbox(
rois=proposal,
bbox_pred=bbox_delta,
im_info=im_info,
name='decode_bbox',
bbox_mean=bbox_mean,
bbox_std=bbox_std,
class_agnostic=class_agnostic
)
cls_score = X.softmax(
cls_logit,
axis=-1,
name='bbox_cls_score'
)
cls_score = X.reshape(
cls_score,
shape=(batch_image, -1, num_class),
name='bbox_cls_score_reshape'
)
return cls_score, bbox_xyxy
|
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")",
"return",
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",",
"bbox_xyxy"
] |
https://github.com/chengzhengxin/groupsoftmax-simpledet/blob/3f63a00998c57fee25241cf43a2e8600893ea462/symbol/builder.py#L394-L430
|
|||
gpodder/mygpo
|
7a028ad621d05d4ca0d58fd22fb92656c8835e43
|
mygpo/podcasts/models.py
|
python
|
Episode.get_episode_number
|
(self, common_title)
|
return int(match.group(1))
|
Number of the episode
|
Number of the episode
|
[
"Number",
"of",
"the",
"episode"
] |
def get_episode_number(self, common_title):
"""Number of the episode"""
if not self.title or not common_title:
return None
title = self.title.replace(common_title, "").strip()
match = re.search(r"^\W*(\d+)", title)
if not match:
return None
return int(match.group(1))
|
[
"def",
"get_episode_number",
"(",
"self",
",",
"common_title",
")",
":",
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"not",
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] |
https://github.com/gpodder/mygpo/blob/7a028ad621d05d4ca0d58fd22fb92656c8835e43/mygpo/podcasts/models.py#L852-L862
|
|
google/macops
|
8442745359c0c941cd4e4e7d243e43bd16b40dec
|
gmacpyutil/gmacpyutil/airport.py
|
python
|
GetDefaultInterface
|
()
|
return CWInterface.interface()
|
Returns the default Wi-Fi interface.
|
Returns the default Wi-Fi interface.
|
[
"Returns",
"the",
"default",
"Wi",
"-",
"Fi",
"interface",
"."
] |
def GetDefaultInterface():
"""Returns the default Wi-Fi interface."""
return CWInterface.interface()
|
[
"def",
"GetDefaultInterface",
"(",
")",
":",
"return",
"CWInterface",
".",
"interface",
"(",
")"
] |
https://github.com/google/macops/blob/8442745359c0c941cd4e4e7d243e43bd16b40dec/gmacpyutil/gmacpyutil/airport.py#L48-L50
|
|
openai/baselines
|
ea25b9e8b234e6ee1bca43083f8f3cf974143998
|
baselines/her/ddpg.py
|
python
|
DDPG.store_episode
|
(self, episode_batch, update_stats=True)
|
episode_batch: array of batch_size x (T or T+1) x dim_key
'o' is of size T+1, others are of size T
|
episode_batch: array of batch_size x (T or T+1) x dim_key
'o' is of size T+1, others are of size T
|
[
"episode_batch",
":",
"array",
"of",
"batch_size",
"x",
"(",
"T",
"or",
"T",
"+",
"1",
")",
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"o",
"is",
"of",
"size",
"T",
"+",
"1",
"others",
"are",
"of",
"size",
"T"
] |
def store_episode(self, episode_batch, update_stats=True):
"""
episode_batch: array of batch_size x (T or T+1) x dim_key
'o' is of size T+1, others are of size T
"""
self.buffer.store_episode(episode_batch)
if update_stats:
# add transitions to normalizer
episode_batch['o_2'] = episode_batch['o'][:, 1:, :]
episode_batch['ag_2'] = episode_batch['ag'][:, 1:, :]
num_normalizing_transitions = transitions_in_episode_batch(episode_batch)
transitions = self.sample_transitions(episode_batch, num_normalizing_transitions)
o, g, ag = transitions['o'], transitions['g'], transitions['ag']
transitions['o'], transitions['g'] = self._preprocess_og(o, ag, g)
# No need to preprocess the o_2 and g_2 since this is only used for stats
self.o_stats.update(transitions['o'])
self.g_stats.update(transitions['g'])
self.o_stats.recompute_stats()
self.g_stats.recompute_stats()
|
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"(",
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] |
https://github.com/openai/baselines/blob/ea25b9e8b234e6ee1bca43083f8f3cf974143998/baselines/her/ddpg.py#L217-L240
|
||
tribe29/checkmk
|
6260f2512e159e311f426e16b84b19d0b8e9ad0c
|
cmk/base/ip_lookup.py
|
python
|
IPLookupCache.__setitem__
|
(self, cache_id: IPLookupCacheId, ipa: HostAddress)
|
Updates the cache with a new / changed entry
When self.persist_on_update update is disabled, this simply updates the in-memory
cache without any persistence interaction. Otherwise:
The cache that was previously loaded into this IPLookupCache with load_persisted()
might be outdated compared to the current persisted lookup cache. Another process
might have updated the cache in the meantime.
The approach here is to load the currently persisted cache with a lock, then update
the current IPLookupCache with it, add the given new / changed entry and then write
out the resulting data structure.
This could really be solved in a better way, but may be sufficient for the moment.
The cache can only be cleaned up with the "Update DNS cache" option in WATO
or the "cmk --update-dns-cache" call that both call update_dns_cache().
|
Updates the cache with a new / changed entry
|
[
"Updates",
"the",
"cache",
"with",
"a",
"new",
"/",
"changed",
"entry"
] |
def __setitem__(self, cache_id: IPLookupCacheId, ipa: HostAddress) -> None:
"""Updates the cache with a new / changed entry
When self.persist_on_update update is disabled, this simply updates the in-memory
cache without any persistence interaction. Otherwise:
The cache that was previously loaded into this IPLookupCache with load_persisted()
might be outdated compared to the current persisted lookup cache. Another process
might have updated the cache in the meantime.
The approach here is to load the currently persisted cache with a lock, then update
the current IPLookupCache with it, add the given new / changed entry and then write
out the resulting data structure.
This could really be solved in a better way, but may be sufficient for the moment.
The cache can only be cleaned up with the "Update DNS cache" option in WATO
or the "cmk --update-dns-cache" call that both call update_dns_cache().
"""
if not self._persist_on_update:
self._cache[cache_id] = ipa
return
with self._store.locked():
self._cache.update(self._store.read_obj(default={}))
self._cache[cache_id] = ipa
self.save_persisted()
|
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"(",
")"
] |
https://github.com/tribe29/checkmk/blob/6260f2512e159e311f426e16b84b19d0b8e9ad0c/cmk/base/ip_lookup.py#L287-L313
|
||
khanhnamle1994/natural-language-processing
|
01d450d5ac002b0156ef4cf93a07cb508c1bcdc5
|
assignment1/.env/lib/python2.7/site-packages/pkg_resources/_vendor/pyparsing.py
|
python
|
ParseResults.pop
|
( self, *args, **kwargs)
|
Removes and returns item at specified index (default=C{last}).
Supports both C{list} and C{dict} semantics for C{pop()}. If passed no
argument or an integer argument, it will use C{list} semantics
and pop tokens from the list of parsed tokens. If passed a
non-integer argument (most likely a string), it will use C{dict}
semantics and pop the corresponding value from any defined
results names. A second default return value argument is
supported, just as in C{dict.pop()}.
Example::
def remove_first(tokens):
tokens.pop(0)
print(OneOrMore(Word(nums)).parseString("0 123 321")) # -> ['0', '123', '321']
print(OneOrMore(Word(nums)).addParseAction(remove_first).parseString("0 123 321")) # -> ['123', '321']
label = Word(alphas)
patt = label("LABEL") + OneOrMore(Word(nums))
print(patt.parseString("AAB 123 321").dump())
# Use pop() in a parse action to remove named result (note that corresponding value is not
# removed from list form of results)
def remove_LABEL(tokens):
tokens.pop("LABEL")
return tokens
patt.addParseAction(remove_LABEL)
print(patt.parseString("AAB 123 321").dump())
prints::
['AAB', '123', '321']
- LABEL: AAB
['AAB', '123', '321']
|
Removes and returns item at specified index (default=C{last}).
Supports both C{list} and C{dict} semantics for C{pop()}. If passed no
argument or an integer argument, it will use C{list} semantics
and pop tokens from the list of parsed tokens. If passed a
non-integer argument (most likely a string), it will use C{dict}
semantics and pop the corresponding value from any defined
results names. A second default return value argument is
supported, just as in C{dict.pop()}.
|
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"C",
"{",
"dict",
".",
"pop",
"()",
"}",
"."
] |
def pop( self, *args, **kwargs):
"""
Removes and returns item at specified index (default=C{last}).
Supports both C{list} and C{dict} semantics for C{pop()}. If passed no
argument or an integer argument, it will use C{list} semantics
and pop tokens from the list of parsed tokens. If passed a
non-integer argument (most likely a string), it will use C{dict}
semantics and pop the corresponding value from any defined
results names. A second default return value argument is
supported, just as in C{dict.pop()}.
Example::
def remove_first(tokens):
tokens.pop(0)
print(OneOrMore(Word(nums)).parseString("0 123 321")) # -> ['0', '123', '321']
print(OneOrMore(Word(nums)).addParseAction(remove_first).parseString("0 123 321")) # -> ['123', '321']
label = Word(alphas)
patt = label("LABEL") + OneOrMore(Word(nums))
print(patt.parseString("AAB 123 321").dump())
# Use pop() in a parse action to remove named result (note that corresponding value is not
# removed from list form of results)
def remove_LABEL(tokens):
tokens.pop("LABEL")
return tokens
patt.addParseAction(remove_LABEL)
print(patt.parseString("AAB 123 321").dump())
prints::
['AAB', '123', '321']
- LABEL: AAB
['AAB', '123', '321']
"""
if not args:
args = [-1]
for k,v in kwargs.items():
if k == 'default':
args = (args[0], v)
else:
raise TypeError("pop() got an unexpected keyword argument '%s'" % k)
if (isinstance(args[0], int) or
len(args) == 1 or
args[0] in self):
index = args[0]
ret = self[index]
del self[index]
return ret
else:
defaultvalue = args[1]
return defaultvalue
|
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"else",
":",
"defaultvalue",
"=",
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"[",
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"]",
"return",
"defaultvalue"
] |
https://github.com/khanhnamle1994/natural-language-processing/blob/01d450d5ac002b0156ef4cf93a07cb508c1bcdc5/assignment1/.env/lib/python2.7/site-packages/pkg_resources/_vendor/pyparsing.py#L488-L538
|
||
francisck/DanderSpritz_docs
|
86bb7caca5a957147f120b18bb5c31f299914904
|
Python/Core/Lib/lib-tk/Tkinter.py
|
python
|
Misc.winfo_atom
|
(self, name, displayof=0)
|
return getint(self.tk.call(args))
|
Return integer which represents atom NAME.
|
Return integer which represents atom NAME.
|
[
"Return",
"integer",
"which",
"represents",
"atom",
"NAME",
"."
] |
def winfo_atom(self, name, displayof=0):
"""Return integer which represents atom NAME."""
args = ('winfo', 'atom') + self._displayof(displayof) + (name,)
return getint(self.tk.call(args))
|
[
"def",
"winfo_atom",
"(",
"self",
",",
"name",
",",
"displayof",
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"0",
")",
":",
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"'winfo'",
",",
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")",
"return",
"getint",
"(",
"self",
".",
"tk",
".",
"call",
"(",
"args",
")",
")"
] |
https://github.com/francisck/DanderSpritz_docs/blob/86bb7caca5a957147f120b18bb5c31f299914904/Python/Core/Lib/lib-tk/Tkinter.py#L767-L770
|
|
pyg-team/pytorch_geometric
|
b920e9a3a64e22c8356be55301c88444ff051cae
|
torch_geometric/datasets/hgb_dataset.py
|
python
|
HGBDataset.download
|
(self)
|
[] |
def download(self):
url = self.url.format(self.names[self.name])
path = download_url(url, self.raw_dir)
extract_zip(path, self.raw_dir)
os.unlink(path)
|
[
"def",
"download",
"(",
"self",
")",
":",
"url",
"=",
"self",
".",
"url",
".",
"format",
"(",
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"[",
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"name",
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")",
"path",
"=",
"download_url",
"(",
"url",
",",
"self",
".",
"raw_dir",
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"extract_zip",
"(",
"path",
",",
"self",
".",
"raw_dir",
")",
"os",
".",
"unlink",
"(",
"path",
")"
] |
https://github.com/pyg-team/pytorch_geometric/blob/b920e9a3a64e22c8356be55301c88444ff051cae/torch_geometric/datasets/hgb_dataset.py#L75-L79
|
||||
zhl2008/awd-platform
|
0416b31abea29743387b10b3914581fbe8e7da5e
|
web_flaskbb/lib/python2.7/site-packages/pip/_vendor/six.py
|
python
|
_SixMetaPathImporter.load_module
|
(self, fullname)
|
return mod
|
[] |
def load_module(self, fullname):
try:
# in case of a reload
return sys.modules[fullname]
except KeyError:
pass
mod = self.__get_module(fullname)
if isinstance(mod, MovedModule):
mod = mod._resolve()
else:
mod.__loader__ = self
sys.modules[fullname] = mod
return mod
|
[
"def",
"load_module",
"(",
"self",
",",
"fullname",
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":",
"try",
":",
"# in case of a reload",
"return",
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"=",
"self",
"sys",
".",
"modules",
"[",
"fullname",
"]",
"=",
"mod",
"return",
"mod"
] |
https://github.com/zhl2008/awd-platform/blob/0416b31abea29743387b10b3914581fbe8e7da5e/web_flaskbb/lib/python2.7/site-packages/pip/_vendor/six.py#L195-L207
|
|||
aimagelab/novelty-detection
|
553cab1757ba18048343929515f65e7c3ca8ff90
|
models/blocks_3d.py
|
python
|
residual_op
|
(x, functions, bns, activation_fn)
|
return activation_fn(out)
|
Implements a global residual operation.
:param x: the input tensor.
:param functions: a list of functions (nn.Modules).
:param bns: a list of optional batch-norm layers.
:param activation_fn: the activation to be applied.
:return: the output of the residual operation.
|
Implements a global residual operation.
|
[
"Implements",
"a",
"global",
"residual",
"operation",
"."
] |
def residual_op(x, functions, bns, activation_fn):
# type: (torch.Tensor, List[Module, Module, Module], List[Module, Module, Module], Module) -> torch.Tensor
"""
Implements a global residual operation.
:param x: the input tensor.
:param functions: a list of functions (nn.Modules).
:param bns: a list of optional batch-norm layers.
:param activation_fn: the activation to be applied.
:return: the output of the residual operation.
"""
f1, f2, f3 = functions
bn1, bn2, bn3 = bns
assert len(functions) == len(bns) == 3
assert f1 is not None and f2 is not None
assert not (f3 is None and bn3 is not None)
# A-branch
ha = x
ha = f1(ha)
if bn1 is not None:
ha = bn1(ha)
ha = activation_fn(ha)
ha = f2(ha)
if bn2 is not None:
ha = bn2(ha)
# B-branch
hb = x
if f3 is not None:
hb = f3(hb)
if bn3 is not None:
hb = bn3(hb)
# Residual connection
out = ha + hb
return activation_fn(out)
|
[
"def",
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"x",
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"+",
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"(",
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] |
https://github.com/aimagelab/novelty-detection/blob/553cab1757ba18048343929515f65e7c3ca8ff90/models/blocks_3d.py#L13-L51
|
|
mdiazcl/fuzzbunch-debian
|
2b76c2249ade83a389ae3badb12a1bd09901fd2c
|
windows/Resources/Python/Core/Lib/bsddb/dbtables.py
|
python
|
bsdTableDB.ListTableColumns
|
(self, table)
|
Return a list of columns in the given table.
[] if the table doesn't exist.
|
Return a list of columns in the given table.
[] if the table doesn't exist.
|
[
"Return",
"a",
"list",
"of",
"columns",
"in",
"the",
"given",
"table",
".",
"[]",
"if",
"the",
"table",
"doesn",
"t",
"exist",
"."
] |
def ListTableColumns(self, table):
"""Return a list of columns in the given table.
[] if the table doesn't exist.
"""
if contains_metastrings(table):
raise ValueError, 'bad table name: contains reserved metastrings'
columnlist_key = _columns_key(table)
if not getattr(self.db, 'has_key')(columnlist_key):
return []
else:
pickledcolumnlist = getattr(self.db, 'get_bytes', self.db.get)(columnlist_key)
if pickledcolumnlist:
return pickle.loads(pickledcolumnlist)
return []
|
[
"def",
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"[",
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] |
https://github.com/mdiazcl/fuzzbunch-debian/blob/2b76c2249ade83a389ae3badb12a1bd09901fd2c/windows/Resources/Python/Core/Lib/bsddb/dbtables.py#L316-L329
|
||
lixinsu/RCZoo
|
37fcb7962fbd4c751c561d4a0c84173881ea8339
|
reader/fusionnet/model.py
|
python
|
DocReader.cuda
|
(self)
|
[] |
def cuda(self):
self.use_cuda = True
self.network = self.network.cuda()
|
[
"def",
"cuda",
"(",
"self",
")",
":",
"self",
".",
"use_cuda",
"=",
"True",
"self",
".",
"network",
"=",
"self",
".",
"network",
".",
"cuda",
"(",
")"
] |
https://github.com/lixinsu/RCZoo/blob/37fcb7962fbd4c751c561d4a0c84173881ea8339/reader/fusionnet/model.py#L487-L489
|
||||
drckf/paysage
|
85ef951be2750e13c0b42121b40e530689bdc1f4
|
paysage/backends/pytorch_backend/rand.py
|
python
|
rand_softmax_units
|
(phi: T.FloatTensor)
|
return on_units
|
Draw random unit values according to softmax probabilities.
Given an effective field vector v,
the softmax probabilities are p = exp(v) / sum(exp(v))
The unit values (the on-units for a 1-hot encoding)
are sampled according to p.
Args:
phi (tensor (batch_size, num_units)): the effective field
Returns:
tensor (batch_size,): random unit values from the softmax distribution.
|
Draw random unit values according to softmax probabilities.
|
[
"Draw",
"random",
"unit",
"values",
"according",
"to",
"softmax",
"probabilities",
"."
] |
def rand_softmax_units(phi: T.FloatTensor) -> T.FloatTensor:
"""
Draw random unit values according to softmax probabilities.
Given an effective field vector v,
the softmax probabilities are p = exp(v) / sum(exp(v))
The unit values (the on-units for a 1-hot encoding)
are sampled according to p.
Args:
phi (tensor (batch_size, num_units)): the effective field
Returns:
tensor (batch_size,): random unit values from the softmax distribution.
"""
max_index = matrix.shape(phi)[1]-1
probs = nl.softmax(phi)
cum_probs = matrix.cumsum(probs, 1)
ref_probs = rand((len(phi), 1))
on_units = matrix.tsum(matrix.cast_long(cum_probs < ref_probs), axis=1,
keepdims=True)
matrix.clip_(on_units, a_min=0, a_max=max_index)
return on_units
|
[
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https://github.com/drckf/paysage/blob/85ef951be2750e13c0b42121b40e530689bdc1f4/paysage/backends/pytorch_backend/rand.py#L145-L169
|
|
openseg-group/OCNet.pytorch
|
812cc57b560fe7fb3b3d9c80da5db80d1e83fbaa
|
eval.py
|
python
|
predict_whole_img
|
(net, image, classes, method, scale)
|
return result
|
Predict the whole image w/o using multiple crops.
The scale specify whether rescale the input image before predicting the results.
|
Predict the whole image w/o using multiple crops.
The scale specify whether rescale the input image before predicting the results.
|
[
"Predict",
"the",
"whole",
"image",
"w",
"/",
"o",
"using",
"multiple",
"crops",
".",
"The",
"scale",
"specify",
"whether",
"rescale",
"the",
"input",
"image",
"before",
"predicting",
"the",
"results",
"."
] |
def predict_whole_img(net, image, classes, method, scale):
"""
Predict the whole image w/o using multiple crops.
The scale specify whether rescale the input image before predicting the results.
"""
N_, C_, H_, W_ = image.shape
if torch_ver == '0.4':
interp = nn.Upsample(size=(H_, W_), mode='bilinear', align_corners=True)
else:
interp = nn.Upsample(size=(H_, W_), mode='bilinear')
if scale != 1:
scaled_img = ndimage.zoom(image, (1.0, 1.0, scale, scale), order=1, prefilter=False)
else:
scaled_img = image
full_prediction_ = net(Variable(torch.from_numpy(scaled_img), volatile=True).cuda(), )
if 'dsn' in method or 'center' in method or 'fuse' in method:
full_prediction = full_prediction_[-1]
else:
full_prediction = full_prediction_
if torch_ver == '0.4':
full_prediction = F.upsample(input=full_prediction, size=(H_, W_), mode='bilinear', align_corners=True)
else:
full_prediction = F.upsample(input=full_prediction, size=(H_, W_), mode='bilinear')
result = full_prediction.cpu().data.numpy().transpose(0,2,3,1)
return result
|
[
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"(",
"0",
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"2",
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"3",
",",
"1",
")",
"return",
"result"
] |
https://github.com/openseg-group/OCNet.pytorch/blob/812cc57b560fe7fb3b3d9c80da5db80d1e83fbaa/eval.py#L139-L165
|
|
sammchardy/python-binance
|
217f1e2205877f80dbaba6ee92354ce4aca74232
|
binance/client.py
|
python
|
Client.get_max_margin_loan
|
(self, **params)
|
return self._request_margin_api('get', 'margin/maxBorrowable', signed=True, data=params)
|
Query max borrow amount for an asset
https://binance-docs.github.io/apidocs/spot/en/#query-max-borrow-user_data
:param asset: required
:type asset: str
:param isolatedSymbol: isolated symbol (if querying isolated margin)
:type isolatedSymbol: str
:param recvWindow: the number of milliseconds the request is valid for
:type recvWindow: int
:returns: API response
{
"amount": "1.69248805"
}
:raises: BinanceRequestException, BinanceAPIException
|
Query max borrow amount for an asset
|
[
"Query",
"max",
"borrow",
"amount",
"for",
"an",
"asset"
] |
def get_max_margin_loan(self, **params):
"""Query max borrow amount for an asset
https://binance-docs.github.io/apidocs/spot/en/#query-max-borrow-user_data
:param asset: required
:type asset: str
:param isolatedSymbol: isolated symbol (if querying isolated margin)
:type isolatedSymbol: str
:param recvWindow: the number of milliseconds the request is valid for
:type recvWindow: int
:returns: API response
{
"amount": "1.69248805"
}
:raises: BinanceRequestException, BinanceAPIException
"""
return self._request_margin_api('get', 'margin/maxBorrowable', signed=True, data=params)
|
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"def",
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"self",
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"True",
",",
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https://github.com/sammchardy/python-binance/blob/217f1e2205877f80dbaba6ee92354ce4aca74232/binance/client.py#L4058-L4079
|
|
ljean/modbus-tk
|
1159c71794071ae67f73f86fa14dd71c989b4859
|
modbus_tk/simulator.py
|
python
|
CompositeServer.start
|
(self)
|
Start the server. It will handle request
|
Start the server. It will handle request
|
[
"Start",
"the",
"server",
".",
"It",
"will",
"handle",
"request"
] |
def start(self):
"""Start the server. It will handle request"""
for srv in self._servers:
srv.start()
|
[
"def",
"start",
"(",
"self",
")",
":",
"for",
"srv",
"in",
"self",
".",
"_servers",
":",
"srv",
".",
"start",
"(",
")"
] |
https://github.com/ljean/modbus-tk/blob/1159c71794071ae67f73f86fa14dd71c989b4859/modbus_tk/simulator.py#L75-L78
|
||
open-cogsci/OpenSesame
|
c4a3641b097a80a76937edbd8c365f036bcc9705
|
opensesame_extensions/undo_manager/undo_manager.py
|
python
|
undo_manager.event_new_item
|
(self, name, _type)
|
desc:
Remember addition of a new item.
|
desc:
Remember addition of a new item.
|
[
"desc",
":",
"Remember",
"addition",
"of",
"a",
"new",
"item",
"."
] |
def event_new_item(self, name, _type):
"""
desc:
Remember addition of a new item.
"""
self.remember_new_item(name)
|
[
"def",
"event_new_item",
"(",
"self",
",",
"name",
",",
"_type",
")",
":",
"self",
".",
"remember_new_item",
"(",
"name",
")"
] |
https://github.com/open-cogsci/OpenSesame/blob/c4a3641b097a80a76937edbd8c365f036bcc9705/opensesame_extensions/undo_manager/undo_manager.py#L70-L77
|
||
fatiando/fatiando
|
ac2afbcb2d99b18f145cc1ed40075beb5f92dd5a
|
fatiando/utils.py
|
python
|
si2eotvos
|
(value)
|
return value * constants.SI2EOTVOS
|
Convert a value from SI units to Eotvos.
Parameters:
* value : number or array
The value in SI
Returns:
* value : number or array
The value in Eotvos
|
Convert a value from SI units to Eotvos.
|
[
"Convert",
"a",
"value",
"from",
"SI",
"units",
"to",
"Eotvos",
"."
] |
def si2eotvos(value):
"""
Convert a value from SI units to Eotvos.
Parameters:
* value : number or array
The value in SI
Returns:
* value : number or array
The value in Eotvos
"""
return value * constants.SI2EOTVOS
|
[
"def",
"si2eotvos",
"(",
"value",
")",
":",
"return",
"value",
"*",
"constants",
".",
"SI2EOTVOS"
] |
https://github.com/fatiando/fatiando/blob/ac2afbcb2d99b18f145cc1ed40075beb5f92dd5a/fatiando/utils.py#L180-L195
|
|
mkusner/grammarVAE
|
ffffe272a8cf1772578dfc92254c55c224cddc02
|
Theano-master/theano/tensor/opt.py
|
python
|
encompasses_broadcastable
|
(b1, b2)
|
return not any(v1 and not v2 for v1, v2 in zip(b1, b2))
|
Parameters
----------
b1
The broadcastable attribute of a tensor type.
b2
The broadcastable attribute of a tensor type.
Returns
-------
bool
True if the broadcastable patterns b1 and b2 are such that b2 is
broadcasted to b1's shape and not the opposite.
|
[] |
def encompasses_broadcastable(b1, b2):
"""
Parameters
----------
b1
The broadcastable attribute of a tensor type.
b2
The broadcastable attribute of a tensor type.
Returns
-------
bool
True if the broadcastable patterns b1 and b2 are such that b2 is
broadcasted to b1's shape and not the opposite.
"""
if len(b1) < len(b2):
return False
b1 = b1[-len(b2):]
return not any(v1 and not v2 for v1, v2 in zip(b1, b2))
|
[
"def",
"encompasses_broadcastable",
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"b1",
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"b2",
")",
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"if",
"len",
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"b1",
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"b1",
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https://github.com/mkusner/grammarVAE/blob/ffffe272a8cf1772578dfc92254c55c224cddc02/Theano-master/theano/tensor/opt.py#L146-L166
|
||
Qiskit/qiskit-terra
|
b66030e3b9192efdd3eb95cf25c6545fe0a13da4
|
qiskit/quantum_info/states/quantum_state.py
|
python
|
QuantumState._subsystem_probabilities
|
(probs, dims, qargs=None)
|
return new_probs
|
Marginalize a probability vector according to subsystems.
Args:
probs (np.array): a probability vector Numpy array.
dims (tuple): subsystem dimensions.
qargs (None or list): a list of subsystems to return
marginalized probabilities for. If None return all
probabilities (Default: None).
Returns:
np.array: the marginalized probability vector flattened
for the specified qargs.
|
Marginalize a probability vector according to subsystems.
|
[
"Marginalize",
"a",
"probability",
"vector",
"according",
"to",
"subsystems",
"."
] |
def _subsystem_probabilities(probs, dims, qargs=None):
"""Marginalize a probability vector according to subsystems.
Args:
probs (np.array): a probability vector Numpy array.
dims (tuple): subsystem dimensions.
qargs (None or list): a list of subsystems to return
marginalized probabilities for. If None return all
probabilities (Default: None).
Returns:
np.array: the marginalized probability vector flattened
for the specified qargs.
"""
if qargs is None:
return probs
# Convert qargs to tensor axes
probs_tens = np.reshape(probs, dims)
ndim = probs_tens.ndim
qargs_axes = [ndim - 1 - i for i in reversed(qargs)]
# Get sum axis for marginalized subsystems
sum_axis = tuple(i for i in range(ndim) if i not in qargs_axes)
if sum_axis:
probs_tens = np.sum(probs_tens, axis=sum_axis)
qargs_axes = np.argsort(np.argsort(qargs_axes))
# Permute probability vector for desired qargs order
probs_tens = np.transpose(probs_tens, axes=qargs_axes)
new_probs = np.reshape(probs_tens, (probs_tens.size,))
return new_probs
|
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https://github.com/Qiskit/qiskit-terra/blob/b66030e3b9192efdd3eb95cf25c6545fe0a13da4/qiskit/quantum_info/states/quantum_state.py#L440-L468
|
|
JiYou/openstack
|
8607dd488bde0905044b303eb6e52bdea6806923
|
packages/source/ceilometer/ceilometer/openstack/common/rpc/impl_qpid.py
|
python
|
DirectPublisher.__init__
|
(self, conf, session, msg_id)
|
Init a 'direct' publisher.
|
Init a 'direct' publisher.
|
[
"Init",
"a",
"direct",
"publisher",
"."
] |
def __init__(self, conf, session, msg_id):
"""Init a 'direct' publisher."""
super(DirectPublisher, self).__init__(session, msg_id,
{"type": "Direct"})
|
[
"def",
"__init__",
"(",
"self",
",",
"conf",
",",
"session",
",",
"msg_id",
")",
":",
"super",
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"DirectPublisher",
",",
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".",
"__init__",
"(",
"session",
",",
"msg_id",
",",
"{",
"\"type\"",
":",
"\"Direct\"",
"}",
")"
] |
https://github.com/JiYou/openstack/blob/8607dd488bde0905044b303eb6e52bdea6806923/packages/source/ceilometer/ceilometer/openstack/common/rpc/impl_qpid.py#L285-L288
|
||
Komodo/KomodoEdit
|
61edab75dce2bdb03943b387b0608ea36f548e8e
|
src/codeintel/lib/codeintel2/css_linter.py
|
python
|
_CSSParser._parse_assignment
|
(self)
|
we saw $var or @var at top-level, expect : expression ;
|
we saw $var or
|
[
"we",
"saw",
"$var",
"or"
] |
def _parse_assignment(self):
"""
we saw $var or @var at top-level, expect : expression ;
"""
self._parse_required_operator(":")
self._parse_expression()
self._parse_required_operator(";")
|
[
"def",
"_parse_assignment",
"(",
"self",
")",
":",
"self",
".",
"_parse_required_operator",
"(",
"\":\"",
")",
"self",
".",
"_parse_expression",
"(",
")",
"self",
".",
"_parse_required_operator",
"(",
"\";\"",
")"
] |
https://github.com/Komodo/KomodoEdit/blob/61edab75dce2bdb03943b387b0608ea36f548e8e/src/codeintel/lib/codeintel2/css_linter.py#L729-L735
|
||
bruderstein/PythonScript
|
df9f7071ddf3a079e3a301b9b53a6dc78cf1208f
|
PythonLib/min/encodings/zlib_codec.py
|
python
|
IncrementalDecoder.__init__
|
(self, errors='strict')
|
[] |
def __init__(self, errors='strict'):
assert errors == 'strict'
self.errors = errors
self.decompressobj = zlib.decompressobj()
|
[
"def",
"__init__",
"(",
"self",
",",
"errors",
"=",
"'strict'",
")",
":",
"assert",
"errors",
"==",
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"errors",
"=",
"errors",
"self",
".",
"decompressobj",
"=",
"zlib",
".",
"decompressobj",
"(",
")"
] |
https://github.com/bruderstein/PythonScript/blob/df9f7071ddf3a079e3a301b9b53a6dc78cf1208f/PythonLib/min/encodings/zlib_codec.py#L44-L47
|
||||
dropbox/dropbox-sdk-python
|
015437429be224732990041164a21a0501235db1
|
dropbox/team_log.py
|
python
|
EventDetails.member_change_status_details
|
(cls, val)
|
return cls('member_change_status_details', val)
|
Create an instance of this class set to the
``member_change_status_details`` tag with value ``val``.
:param MemberChangeStatusDetails val:
:rtype: EventDetails
|
Create an instance of this class set to the
``member_change_status_details`` tag with value ``val``.
|
[
"Create",
"an",
"instance",
"of",
"this",
"class",
"set",
"to",
"the",
"member_change_status_details",
"tag",
"with",
"value",
"val",
"."
] |
def member_change_status_details(cls, val):
"""
Create an instance of this class set to the
``member_change_status_details`` tag with value ``val``.
:param MemberChangeStatusDetails val:
:rtype: EventDetails
"""
return cls('member_change_status_details', val)
|
[
"def",
"member_change_status_details",
"(",
"cls",
",",
"val",
")",
":",
"return",
"cls",
"(",
"'member_change_status_details'",
",",
"val",
")"
] |
https://github.com/dropbox/dropbox-sdk-python/blob/015437429be224732990041164a21a0501235db1/dropbox/team_log.py#L9620-L9628
|
|
descarteslabs/descarteslabs-python
|
ace8a1a89d58b75df1bcaa613a4b3544d7bdc4be
|
descarteslabs/vectors/featurecollection.py
|
python
|
FeatureCollection.list_exports
|
(self)
|
return results
|
Get all the export tasks for this product.
Returns
-------
list(:class:`ExportTask <descarteslabs.common.tasks.exporttask.ExportTask>`)
The list of tasks for the product.
Raises
------
~descarteslabs.client.exceptions.NotFoundError
Raised if the product cannot be found.
~descarteslabs.client.exceptions.RateLimitError
Raised when too many requests have been made within a given time period.
~descarteslabs.client.exceptions.ServerError
Raised when a unknown error occurred on the server.
Example
-------
>>> from descarteslabs.vectors import FeatureCollection, properties as p
>>> aoi_geometry = {
... "type": "Polygon",
... "coordinates": [[ # A small area in Washington DC
... [-77.05501556396483, 38.90946877327506],
... [-77.0419692993164, 38.90946877327506],
... [-77.0419692993164, 38.91855139233948],
... [-77.05501556396483, 38.91855139233948],
... [-77.05501556396483, 38.90946877327506]
... ]]
... }
>>> buildings = FeatureCollection(
... "a35126a241bd022c026e96ab9fe5e0ea23967d08:USBuildingFootprints") # doctest: +SKIP
>>> filtered_buildings = buildings.filter(geometry=aoi_geometry) # doctest: +SKIP
>>> task = filtered_buildings.export("my_export") # doctest: +SKIP
>>> exports = filtered_buildings.list_exports() # doctest: +SKIP
|
Get all the export tasks for this product.
|
[
"Get",
"all",
"the",
"export",
"tasks",
"for",
"this",
"product",
"."
] |
def list_exports(self):
"""
Get all the export tasks for this product.
Returns
-------
list(:class:`ExportTask <descarteslabs.common.tasks.exporttask.ExportTask>`)
The list of tasks for the product.
Raises
------
~descarteslabs.client.exceptions.NotFoundError
Raised if the product cannot be found.
~descarteslabs.client.exceptions.RateLimitError
Raised when too many requests have been made within a given time period.
~descarteslabs.client.exceptions.ServerError
Raised when a unknown error occurred on the server.
Example
-------
>>> from descarteslabs.vectors import FeatureCollection, properties as p
>>> aoi_geometry = {
... "type": "Polygon",
... "coordinates": [[ # A small area in Washington DC
... [-77.05501556396483, 38.90946877327506],
... [-77.0419692993164, 38.90946877327506],
... [-77.0419692993164, 38.91855139233948],
... [-77.05501556396483, 38.91855139233948],
... [-77.05501556396483, 38.90946877327506]
... ]]
... }
>>> buildings = FeatureCollection(
... "a35126a241bd022c026e96ab9fe5e0ea23967d08:USBuildingFootprints") # doctest: +SKIP
>>> filtered_buildings = buildings.filter(geometry=aoi_geometry) # doctest: +SKIP
>>> task = filtered_buildings.export("my_export") # doctest: +SKIP
>>> exports = filtered_buildings.list_exports() # doctest: +SKIP
"""
results = []
for result in self.vector_client.get_export_results(self.id):
results.append(
ExportTask(
self.id,
tuid=result.id,
result_attrs=result.attributes,
client=self.vector_client,
)
)
return results
|
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"[",
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"(",
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",",
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"attributes",
",",
"client",
"=",
"self",
".",
"vector_client",
",",
")",
")",
"return",
"results"
] |
https://github.com/descarteslabs/descarteslabs-python/blob/ace8a1a89d58b75df1bcaa613a4b3544d7bdc4be/descarteslabs/vectors/featurecollection.py#L956-L1006
|
|
andresriancho/w3af
|
cd22e5252243a87aaa6d0ddea47cf58dacfe00a9
|
w3af/core/data/url/handlers/ntlm_auth.py
|
python
|
HTTPNtlmAuthHandler.http_error_401
|
(self, req, fp, code, msg, headers)
|
return response
|
[] |
def http_error_401(self, req, fp, code, msg, headers):
url = req.get_full_url()
response = self.http_error_auth_reqed('www-authenticate',
url, req, headers)
self.reset_retry_count()
return response
|
[
"def",
"http_error_401",
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"self",
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",",
"fp",
",",
"code",
",",
"msg",
",",
"headers",
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":",
"url",
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")",
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",",
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",",
"req",
",",
"headers",
")",
"self",
".",
"reset_retry_count",
"(",
")",
"return",
"response"
] |
https://github.com/andresriancho/w3af/blob/cd22e5252243a87aaa6d0ddea47cf58dacfe00a9/w3af/core/data/url/handlers/ntlm_auth.py#L97-L102
|
|||
DataDog/integrations-core
|
934674b29d94b70ccc008f76ea172d0cdae05e1e
|
sqlserver/datadog_checks/sqlserver/config_models/defaults.py
|
python
|
shared_custom_metrics
|
(field, value)
|
return get_default_field_value(field, value)
|
[] |
def shared_custom_metrics(field, value):
return get_default_field_value(field, value)
|
[
"def",
"shared_custom_metrics",
"(",
"field",
",",
"value",
")",
":",
"return",
"get_default_field_value",
"(",
"field",
",",
"value",
")"
] |
https://github.com/DataDog/integrations-core/blob/934674b29d94b70ccc008f76ea172d0cdae05e1e/sqlserver/datadog_checks/sqlserver/config_models/defaults.py#L13-L14
|
|||
XaF/TraktForVLC
|
7851368d7ce62a15bb245fc078f3eab201c12357
|
version.py
|
python
|
CIVersionReader.check_tag
|
(self, tag=None, abbrev=7)
|
[] |
def check_tag(self, tag=None, abbrev=7):
if not tag:
tag = self.call_git_describe(abbrev, exact=True)
# If we did not find any version, we can return now, there
# is no tag to check
if not tag:
raise GitVersionException(
'No tag found for the current commit.')
if not self.pep440_public_version.search(tag):
raise GitVersionException(
'Version {} does not match PEP440 for public version '
'identifiers.'.format(tag))
|
[
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] |
https://github.com/XaF/TraktForVLC/blob/7851368d7ce62a15bb245fc078f3eab201c12357/version.py#L202-L215
|
||||
kiibohd/kll
|
b6d997b810006326d31fc570c89d396fd0b70569
|
kll/common/stage.py
|
python
|
FileImportStage.command_line_flags
|
(self, parser)
|
Group parser for command line options
@param parser: argparse setup object
|
Group parser for command line options
|
[
"Group",
"parser",
"for",
"command",
"line",
"options"
] |
def command_line_flags(self, parser):
'''
Group parser for command line options
@param parser: argparse setup object
'''
# Create new option group
group = parser.add_argument_group('\033[1mFile Context Configuration\033[0m')
# Positional Arguments
group.add_argument('generic', type=str, nargs='*', default=self.generic_files,
help="Auto-detect context of .kll files, defaults to a base map configuration."
)
# Optional Arguments
group.add_argument('--config', type=str, nargs='+', default=self.config_files,
help="Specify base configuration .kll files, earliest priority"
)
group.add_argument('--base', type=str, nargs='+', default=self.base_files,
help="Specify base map configuration, applied after config .kll files.\n"
"The base map is applied prior to all default and partial maps and is used as the basis for them."
)
group.add_argument('--default', type=str, nargs='+', default=self.default_files,
help="Specify .kll files to layer on top of the default map to create a combined map.\n"
"Also known as layer 0."
)
group.add_argument('--partial', type=str, nargs='+', action='append', default=self.partial_files,
help="Specify .kll files to generate partial map, multiple files per flag.\n"
"Each -p defines another partial map.\n"
"Base .kll files (that define the scan code maps) must be defined for each partial map."
)
|
[
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":",
"# Create new option group",
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"\"Each -p defines another partial map.\\n\"",
"\"Base .kll files (that define the scan code maps) must be defined for each partial map.\"",
")"
] |
https://github.com/kiibohd/kll/blob/b6d997b810006326d31fc570c89d396fd0b70569/kll/common/stage.py#L344-L374
|
||
matplotlib/matplotlib
|
8d7a2b9d2a38f01ee0d6802dd4f9e98aec812322
|
lib/matplotlib/backends/backend_pdf.py
|
python
|
_create_pdf_info_dict
|
(backend, metadata)
|
return info
|
Create a PDF infoDict based on user-supplied metadata.
A default ``Creator``, ``Producer``, and ``CreationDate`` are added, though
the user metadata may override it. The date may be the current time, or a
time set by the ``SOURCE_DATE_EPOCH`` environment variable.
Metadata is verified to have the correct keys and their expected types. Any
unknown keys/types will raise a warning.
Parameters
----------
backend : str
The name of the backend to use in the Producer value.
metadata : dict[str, Union[str, datetime, Name]]
A dictionary of metadata supplied by the user with information
following the PDF specification, also defined in
`~.backend_pdf.PdfPages` below.
If any value is *None*, then the key will be removed. This can be used
to remove any pre-defined values.
Returns
-------
dict[str, Union[str, datetime, Name]]
A validated dictionary of metadata.
|
Create a PDF infoDict based on user-supplied metadata.
|
[
"Create",
"a",
"PDF",
"infoDict",
"based",
"on",
"user",
"-",
"supplied",
"metadata",
"."
] |
def _create_pdf_info_dict(backend, metadata):
"""
Create a PDF infoDict based on user-supplied metadata.
A default ``Creator``, ``Producer``, and ``CreationDate`` are added, though
the user metadata may override it. The date may be the current time, or a
time set by the ``SOURCE_DATE_EPOCH`` environment variable.
Metadata is verified to have the correct keys and their expected types. Any
unknown keys/types will raise a warning.
Parameters
----------
backend : str
The name of the backend to use in the Producer value.
metadata : dict[str, Union[str, datetime, Name]]
A dictionary of metadata supplied by the user with information
following the PDF specification, also defined in
`~.backend_pdf.PdfPages` below.
If any value is *None*, then the key will be removed. This can be used
to remove any pre-defined values.
Returns
-------
dict[str, Union[str, datetime, Name]]
A validated dictionary of metadata.
"""
# get source date from SOURCE_DATE_EPOCH, if set
# See https://reproducible-builds.org/specs/source-date-epoch/
source_date_epoch = os.getenv("SOURCE_DATE_EPOCH")
if source_date_epoch:
source_date = datetime.utcfromtimestamp(int(source_date_epoch))
source_date = source_date.replace(tzinfo=UTC)
else:
source_date = datetime.today()
info = {
'Creator': f'Matplotlib v{mpl.__version__}, https://matplotlib.org',
'Producer': f'Matplotlib {backend} backend v{mpl.__version__}',
'CreationDate': source_date,
**metadata
}
info = {k: v for (k, v) in info.items() if v is not None}
def is_string_like(x):
return isinstance(x, str)
is_string_like.text_for_warning = "an instance of str"
def is_date(x):
return isinstance(x, datetime)
is_date.text_for_warning = "an instance of datetime.datetime"
def check_trapped(x):
if isinstance(x, Name):
return x.name in (b'True', b'False', b'Unknown')
else:
return x in ('True', 'False', 'Unknown')
check_trapped.text_for_warning = 'one of {"True", "False", "Unknown"}'
keywords = {
'Title': is_string_like,
'Author': is_string_like,
'Subject': is_string_like,
'Keywords': is_string_like,
'Creator': is_string_like,
'Producer': is_string_like,
'CreationDate': is_date,
'ModDate': is_date,
'Trapped': check_trapped,
}
for k in info:
if k not in keywords:
_api.warn_external(f'Unknown infodict keyword: {k!r}. '
f'Must be one of {set(keywords)!r}.')
elif not keywords[k](info[k]):
_api.warn_external(f'Bad value for infodict keyword {k}. '
f'Got {info[k]!r} which is not '
f'{keywords[k].text_for_warning}.')
if 'Trapped' in info:
info['Trapped'] = Name(info['Trapped'])
return info
|
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"f'{keywords[k].text_for_warning}.'",
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"=",
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"(",
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")",
"return",
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] |
https://github.com/matplotlib/matplotlib/blob/8d7a2b9d2a38f01ee0d6802dd4f9e98aec812322/lib/matplotlib/backends/backend_pdf.py#L139-L223
|
|
CATIA-Systems/FMPy
|
fde192346c36eb69dbaca60a96e80cdc8ef37b89
|
fmpy/util.py
|
python
|
plot_result
|
(result, reference=None, names=None, filename=None, window_title=None, events=False)
|
Plot a collection of time series.
Parameters:
result: structured NumPy Array that contains the time series to plot where 'time' is the independent variable
reference: optional reference signals with the same structure as `result`
names: variables to plot
filename: when provided the plot is saved as `filename` instead of showing the figure
window_title: title for the figure window
events: draw vertical lines at events
|
Plot a collection of time series.
|
[
"Plot",
"a",
"collection",
"of",
"time",
"series",
"."
] |
def plot_result(result, reference=None, names=None, filename=None, window_title=None, events=False):
""" Plot a collection of time series.
Parameters:
result: structured NumPy Array that contains the time series to plot where 'time' is the independent variable
reference: optional reference signals with the same structure as `result`
names: variables to plot
filename: when provided the plot is saved as `filename` instead of showing the figure
window_title: title for the figure window
events: draw vertical lines at events
"""
from . import plot_library
if plot_library == 'plotly':
figure = create_plotly_figure(result, names=names, events=events)
if filename is None:
figure.show()
else:
figure.write_image(filename)
return
import matplotlib.pylab as pylab
import matplotlib.pyplot as plt
import matplotlib.transforms as mtransforms
from matplotlib.ticker import MaxNLocator
from collections.abc import Iterable
params = {
'legend.fontsize': 8,
'axes.labelsize': 8,
'xtick.labelsize': 8,
'ytick.labelsize': 8,
'axes.linewidth': 0.5,
}
pylab.rcParams.update(params)
time = result['time']
if names is None:
names = []
# plot at most 20 one-dimensional signals
for d in result.dtype.descr[1:]:
if len(d) < 3 and len(names) < 20:
names.append(d[0])
if len(names) > 0:
# indent label 0.015 inch / character
label_x = -0.015 * np.max(list(map(len, names)) + [8])
fig, axes = plt.subplots(len(names), sharex=True)
fig.set_facecolor('white')
if not isinstance(axes, Iterable):
axes = [axes]
if events:
t_event = time[np.argwhere(np.diff(time) == 0)]
for ax, name in zip(axes, names):
y = result[name]
ax.grid(b=True, which='both', color='0.8', linestyle='-', zorder=0)
ax.tick_params(direction='in')
if events:
for t in t_event:
ax.axvline(x=t, color='y', linewidth=1)
if reference is not None and name in reference.dtype.names:
t_ref = reference[reference.dtype.names[0]]
y_ref = reference[name]
t_band, y_min, y_max, i_out = validate_signal(t=time, y=y, t_ref=t_ref, y_ref=y_ref)
ax.fill_between(t_band, y_min, y_max, facecolor=(0, 0.5, 0), alpha=0.1)
ax.plot(t_band, y_min, color=(0, 0.5, 0), linewidth=1, label='lower bound', zorder=101, alpha=0.5)
ax.plot(t_band, y_max, color=(0, 0.5, 0), linewidth=1, label='upper bound', zorder=101, alpha=0.5)
# mark the outliers
# use the data coordinates for the x-axis and the axes coordinates for the y-axis
trans = mtransforms.blended_transform_factory(ax.transData, ax.transAxes)
ax.fill_between(time, 0, 1, where=i_out, facecolor='red', alpha=0.5, transform=trans)
if y.dtype == np.float64:
# find left indices of discontinuities
i_disc = np.flatnonzero(np.diff(time) == 0)
i_disc = np.append(i_disc + 1, len(time))
i0 = 0
for i1 in i_disc:
ax.plot(time[i0:i1], y[i0:i1], color='b', linewidth=0.9, label='result', zorder=101)
i0 = i1
else:
ax.hlines(y[:-1], time[:-1], time[1:], colors='b', linewidth=1, label='result', zorder=101)
ax.yaxis.set_major_locator(MaxNLocator(integer=True))
if y.dtype == bool:
# use fixed range and labels and fill area
ax.set_ylim(-0.25, 1.25)
ax.yaxis.set_ticks([0, 1])
ax.yaxis.set_ticklabels(['false', 'true'])
if y.ndim == 1:
ax.fill_between(time, y, 0, step='post', facecolor='b', alpha=0.1)
else:
ax.margins(x=0, y=0.05)
if time.size < 200:
ax.scatter(time, y, color='b', s=5, zorder=101)
ax.set_ylabel(name, horizontalalignment='left', rotation=0)
# align the y-labels
ax.get_yaxis().set_label_coords(label_x, 0.5)
# set the window title
if window_title is not None:
fig.canvas.set_window_title(window_title)
def onresize(event):
fig = plt.gcf()
w = fig.get_figwidth()
# tight_layout() crashes on very small figures
if w < 3:
return
x = label_x * (8.0 / w)
# update label coordinates
for ax in fig.get_axes():
ax.get_yaxis().set_label_coords(x, 0.5)
# update layout
plt.tight_layout()
# update layout when the plot is re-sized
fig.canvas.mpl_connect('resize_event', onresize)
fig.set_size_inches(w=8, h=1.5 * len(names), forward=True)
plt.tight_layout()
if filename is None:
plt.show()
else:
dir, _ = os.path.split(filename)
if not os.path.isdir(dir):
os.makedirs(dir)
fig.savefig(filename)
plt.close(fig)
|
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] |
https://github.com/CATIA-Systems/FMPy/blob/fde192346c36eb69dbaca60a96e80cdc8ef37b89/fmpy/util.py#L348-L505
|
||
pymedusa/Medusa
|
1405fbb6eb8ef4d20fcca24c32ddca52b11f0f38
|
medusa/name_parser/rules/rules.py
|
python
|
OnePreGroupAsMultiEpisode.when
|
(self, matches, context)
|
return to_remove, to_append
|
Evaluate the rule.
:param matches:
:type matches: rebulk.match.Matches
:param context:
:type context: dict
:return:
|
Evaluate the rule.
|
[
"Evaluate",
"the",
"rule",
"."
] |
def when(self, matches, context):
"""Evaluate the rule.
:param matches:
:type matches: rebulk.match.Matches
:param context:
:type context: dict
:return:
"""
titles = matches.named('title')
if not titles:
return
episodes = matches.named('episode')
if not episodes or len(episodes) != 2:
return
is_anime = context.get('show_type') == 'anime' or matches.tagged('anime')
if is_anime or matches.named('season'):
return
sorted_episodes = sorted(episodes)
if sorted_episodes[-1].value != 1:
return
episode = copy.copy(sorted_episodes[0])
episode.name = 'absolute_episode'
to_remove = [sorted_episodes[-1]]
to_append = [episode]
episode_titles = matches.named('episode_title')
if episode_titles:
release_group = copy.copy(episode_titles[0])
release_group.name = 'release_group'
to_remove.append(episode_titles[0])
to_append.append(release_group)
return to_remove, to_append
|
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] |
https://github.com/pymedusa/Medusa/blob/1405fbb6eb8ef4d20fcca24c32ddca52b11f0f38/medusa/name_parser/rules/rules.py#L825-L864
|
|
saltstack/salt
|
fae5bc757ad0f1716483ce7ae180b451545c2058
|
salt/ext/tornado/websocket.py
|
python
|
WebSocketHandler.ping
|
(self, data)
|
Send ping frame to the remote end.
|
Send ping frame to the remote end.
|
[
"Send",
"ping",
"frame",
"to",
"the",
"remote",
"end",
"."
] |
def ping(self, data):
"""Send ping frame to the remote end."""
if self.ws_connection is None:
raise WebSocketClosedError()
self.ws_connection.write_ping(data)
|
[
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")",
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".",
"write_ping",
"(",
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")"
] |
https://github.com/saltstack/salt/blob/fae5bc757ad0f1716483ce7ae180b451545c2058/salt/ext/tornado/websocket.py#L312-L316
|
||
mypaint/mypaint
|
90b36dbc7b8bd2f323383f7edf608a5e0a3a1a33
|
gui/drawwindow.py
|
python
|
DrawWindow._display_filter_radioaction_changed_cb
|
(self, action, newaction)
|
Handle changes to the Display Filter radioaction set.
|
Handle changes to the Display Filter radioaction set.
|
[
"Handle",
"changes",
"to",
"the",
"Display",
"Filter",
"radioaction",
"set",
"."
] |
def _display_filter_radioaction_changed_cb(self, action, newaction):
"""Handle changes to the Display Filter radioaction set."""
newaction_name = newaction.get_name()
newfilter = {
"DisplayFilterNone": None,
"DisplayFilterLumaOnly": gui.displayfilter.luma_only,
"DisplayFilterInvertColors": gui.displayfilter.invert_colors,
"DisplayFilterSimDeuteranopia": gui.displayfilter.sim_deuteranopia,
"DisplayFilterSimProtanopia": gui.displayfilter.sim_protanopia,
"DisplayFilterSimTritanopia": gui.displayfilter.sim_tritanopia,
}.get(newaction_name)
for tdw in gui.tileddrawwidget.TiledDrawWidget.get_visible_tdws():
if tdw.renderer.display_filter is newfilter:
continue
logger.debug("Updating display_filter on %r to %r", tdw, newfilter)
tdw.renderer.display_filter = newfilter
tdw.queue_draw()
|
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] |
https://github.com/mypaint/mypaint/blob/90b36dbc7b8bd2f323383f7edf608a5e0a3a1a33/gui/drawwindow.py#L874-L890
|
||
numenta/nupic
|
b9ebedaf54f49a33de22d8d44dff7c765cdb5548
|
src/nupic/algorithms/fdrutilities.py
|
python
|
_listOfOnTimesInVec
|
(vector)
|
return (totalOnTime, numOnTimes, durations)
|
Returns 3 things for a vector:
* the total on time
* the number of runs
* a list of the durations of each run.
Parameters:
-----------------------------------------------
input stream: 11100000001100000000011111100000
return value: (11, 3, [3, 2, 6])
|
Returns 3 things for a vector:
* the total on time
* the number of runs
* a list of the durations of each run.
|
[
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"a",
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"runs",
"*",
"a",
"list",
"of",
"the",
"durations",
"of",
"each",
"run",
"."
] |
def _listOfOnTimesInVec(vector):
"""
Returns 3 things for a vector:
* the total on time
* the number of runs
* a list of the durations of each run.
Parameters:
-----------------------------------------------
input stream: 11100000001100000000011111100000
return value: (11, 3, [3, 2, 6])
"""
# init counters
durations = []
numOnTimes = 0
totalOnTime = 0
# Find where the nonzeros are
nonzeros = numpy.array(vector).nonzero()[0]
# Nothing to do if vector is empty
if len(nonzeros) == 0:
return (0, 0, [])
# Special case of only 1 on bit
if len(nonzeros) == 1:
return (1, 1, [1])
# Count the consecutive non-zeros
prev = nonzeros[0]
onTime = 1
endIdx = nonzeros[-1]
for idx in nonzeros[1:]:
if idx != prev+1:
totalOnTime += onTime
numOnTimes += 1
durations.append(onTime)
onTime = 1
else:
onTime += 1
prev = idx
# Add in the last one
totalOnTime += onTime
numOnTimes += 1
durations.append(onTime)
return (totalOnTime, numOnTimes, durations)
|
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",",
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",",
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")"
] |
https://github.com/numenta/nupic/blob/b9ebedaf54f49a33de22d8d44dff7c765cdb5548/src/nupic/algorithms/fdrutilities.py#L848-L896
|
|
hamcrest/PyHamcrest
|
11aafabd688af2db23e8614f89da3015fd39f611
|
src/hamcrest/core/core/raises.py
|
python
|
DeferredCallable.with_args
|
(self, *args, **kwargs)
|
return self
|
[] |
def with_args(self, *args, **kwargs):
self.args = args
self.kwargs = kwargs
return self
|
[
"def",
"with_args",
"(",
"self",
",",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"self",
".",
"args",
"=",
"args",
"self",
".",
"kwargs",
"=",
"kwargs",
"return",
"self"
] |
https://github.com/hamcrest/PyHamcrest/blob/11aafabd688af2db23e8614f89da3015fd39f611/src/hamcrest/core/core/raises.py#L124-L127
|
|||
LinOTP/LinOTP
|
bb3940bbaccea99550e6c063ff824f258dd6d6d7
|
linotp/lib/userservice.py
|
python
|
get_cookie_expiry
|
()
|
return config.get("selfservice.auth_expiry", False)
|
get the cookie encryption expiry from the config
- if the selfservice is dropped from running locally, this
configuration option might not exist anymore
:return: return the cookie encryption expiry
|
get the cookie encryption expiry from the config
- if the selfservice is dropped from running locally, this
configuration option might not exist anymore
|
[
"get",
"the",
"cookie",
"encryption",
"expiry",
"from",
"the",
"config",
"-",
"if",
"the",
"selfservice",
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"dropped",
"from",
"running",
"locally",
"this",
"configuration",
"option",
"might",
"not",
"exist",
"anymore"
] |
def get_cookie_expiry():
"""
get the cookie encryption expiry from the config
- if the selfservice is dropped from running locally, this
configuration option might not exist anymore
:return: return the cookie encryption expiry
"""
config = request_context["Config"]
return config.get("selfservice.auth_expiry", False)
|
[
"def",
"get_cookie_expiry",
"(",
")",
":",
"config",
"=",
"request_context",
"[",
"\"Config\"",
"]",
"return",
"config",
".",
"get",
"(",
"\"selfservice.auth_expiry\"",
",",
"False",
")"
] |
https://github.com/LinOTP/LinOTP/blob/bb3940bbaccea99550e6c063ff824f258dd6d6d7/linotp/lib/userservice.py#L263-L273
|
|
scipy/scipy
|
e0a749f01e79046642ccfdc419edbf9e7ca141ad
|
scipy/stats/_stats_py.py
|
python
|
relfreq
|
(a, numbins=10, defaultreallimits=None, weights=None)
|
return RelfreqResult(h, l, b, e)
|
Return a relative frequency histogram, using the histogram function.
A relative frequency histogram is a mapping of the number of
observations in each of the bins relative to the total of observations.
Parameters
----------
a : array_like
Input array.
numbins : int, optional
The number of bins to use for the histogram. Default is 10.
defaultreallimits : tuple (lower, upper), optional
The lower and upper values for the range of the histogram.
If no value is given, a range slightly larger than the range of the
values in a is used. Specifically ``(a.min() - s, a.max() + s)``,
where ``s = (1/2)(a.max() - a.min()) / (numbins - 1)``.
weights : array_like, optional
The weights for each value in `a`. Default is None, which gives each
value a weight of 1.0
Returns
-------
frequency : ndarray
Binned values of relative frequency.
lowerlimit : float
Lower real limit.
binsize : float
Width of each bin.
extrapoints : int
Extra points.
Examples
--------
>>> import matplotlib.pyplot as plt
>>> from numpy.random import default_rng
>>> from scipy import stats
>>> rng = default_rng()
>>> a = np.array([2, 4, 1, 2, 3, 2])
>>> res = stats.relfreq(a, numbins=4)
>>> res.frequency
array([ 0.16666667, 0.5 , 0.16666667, 0.16666667])
>>> np.sum(res.frequency) # relative frequencies should add up to 1
1.0
Create a normal distribution with 1000 random values
>>> samples = stats.norm.rvs(size=1000, random_state=rng)
Calculate relative frequencies
>>> res = stats.relfreq(samples, numbins=25)
Calculate space of values for x
>>> x = res.lowerlimit + np.linspace(0, res.binsize*res.frequency.size,
... res.frequency.size)
Plot relative frequency histogram
>>> fig = plt.figure(figsize=(5, 4))
>>> ax = fig.add_subplot(1, 1, 1)
>>> ax.bar(x, res.frequency, width=res.binsize)
>>> ax.set_title('Relative frequency histogram')
>>> ax.set_xlim([x.min(), x.max()])
>>> plt.show()
|
Return a relative frequency histogram, using the histogram function.
|
[
"Return",
"a",
"relative",
"frequency",
"histogram",
"using",
"the",
"histogram",
"function",
"."
] |
def relfreq(a, numbins=10, defaultreallimits=None, weights=None):
"""Return a relative frequency histogram, using the histogram function.
A relative frequency histogram is a mapping of the number of
observations in each of the bins relative to the total of observations.
Parameters
----------
a : array_like
Input array.
numbins : int, optional
The number of bins to use for the histogram. Default is 10.
defaultreallimits : tuple (lower, upper), optional
The lower and upper values for the range of the histogram.
If no value is given, a range slightly larger than the range of the
values in a is used. Specifically ``(a.min() - s, a.max() + s)``,
where ``s = (1/2)(a.max() - a.min()) / (numbins - 1)``.
weights : array_like, optional
The weights for each value in `a`. Default is None, which gives each
value a weight of 1.0
Returns
-------
frequency : ndarray
Binned values of relative frequency.
lowerlimit : float
Lower real limit.
binsize : float
Width of each bin.
extrapoints : int
Extra points.
Examples
--------
>>> import matplotlib.pyplot as plt
>>> from numpy.random import default_rng
>>> from scipy import stats
>>> rng = default_rng()
>>> a = np.array([2, 4, 1, 2, 3, 2])
>>> res = stats.relfreq(a, numbins=4)
>>> res.frequency
array([ 0.16666667, 0.5 , 0.16666667, 0.16666667])
>>> np.sum(res.frequency) # relative frequencies should add up to 1
1.0
Create a normal distribution with 1000 random values
>>> samples = stats.norm.rvs(size=1000, random_state=rng)
Calculate relative frequencies
>>> res = stats.relfreq(samples, numbins=25)
Calculate space of values for x
>>> x = res.lowerlimit + np.linspace(0, res.binsize*res.frequency.size,
... res.frequency.size)
Plot relative frequency histogram
>>> fig = plt.figure(figsize=(5, 4))
>>> ax = fig.add_subplot(1, 1, 1)
>>> ax.bar(x, res.frequency, width=res.binsize)
>>> ax.set_title('Relative frequency histogram')
>>> ax.set_xlim([x.min(), x.max()])
>>> plt.show()
"""
a = np.asanyarray(a)
h, l, b, e = _histogram(a, numbins, defaultreallimits, weights=weights)
h = h / a.shape[0]
return RelfreqResult(h, l, b, e)
|
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"h",
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",",
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",",
"e",
")"
] |
https://github.com/scipy/scipy/blob/e0a749f01e79046642ccfdc419edbf9e7ca141ad/scipy/stats/_stats_py.py#L2086-L2159
|
|
sdaps/sdaps
|
51d1072185223f5e48512661e2c1e8399d63e876
|
sdaps/recognize/buddies.py
|
python
|
Checkbox.get_outline_mask
|
(self)
|
return surf, xoff, yoff
|
[] |
def get_outline_mask(self):
cr, surf, line_width, width, height, xoff, yoff = self.prepare_mask()
if self.obj.form == "ellipse":
cr.save()
cr.scale((width - line_width) / 2.0, (height - line_width) / 2.0)
cr.arc(0, 0, 1.0, 0, 2*math.pi)
# Restore old matrix (without removing the current path)
cr.restore()
else:
cr.translate(-0.5 * width, -0.5 * height)
cr.rectangle(line_width / 2, line_width / 2, width - line_width / 2, height - line_width / 2)
cr.stroke()
surf.flush()
del cr
return surf, xoff, yoff
|
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https://github.com/sdaps/sdaps/blob/51d1072185223f5e48512661e2c1e8399d63e876/sdaps/recognize/buddies.py#L613-L632
|
|||
cdent/gabbi
|
73dd8996ef4c7a9b50eb70532f830b71d41a1225
|
gabbi/handlers/jsonhandler.py
|
python
|
JSONHandler.action
|
(self, test, path, value=None)
|
Test json_paths against json data.
|
Test json_paths against json data.
|
[
"Test",
"json_paths",
"against",
"json",
"data",
"."
] |
def action(self, test, path, value=None):
"""Test json_paths against json data."""
# Do template expansion in the left hand side.
lhs_path = test.replace_template(path)
rhs_path = rhs_match = None
try:
lhs_match = self.extract_json_path_value(
test.response_data, lhs_path)
except AttributeError:
raise AssertionError('unable to extract JSON from test results')
except ValueError:
raise AssertionError('left hand side json path %s cannot match '
'%s' % (path, test.response_data))
# read data from disk if the value starts with '<@'
if isinstance(value, six.string_types) and value.startswith('<@'):
# Do template expansion in the rhs if rhs_path is provided.
if ':' in value:
value, rhs_path = value.split(':$', 1)
rhs_path = test.replace_template('$' + rhs_path)
value = self.load_data_file(test, value.replace('<@', '', 1))
if rhs_path:
try:
rhs_match = self.extract_json_path_value(value, rhs_path)
except AttributeError:
raise AssertionError('unable to extract JSON from data on '
'disk')
except ValueError:
raise AssertionError('right hand side json path %s cannot '
'match %s' % (rhs_path, value))
# If expected is a string, check to see if it is a regex.
is_regex = (isinstance(value, six.string_types) and
value.startswith('/') and
value.endswith('/') and
len(value) > 1)
expected = (rhs_match or
test.replace_template(value, escape_regex=is_regex))
match = lhs_match
if is_regex and not rhs_match:
expected = expected[1:-1]
# match may be a number so stringify
match = six.text_type(match)
test.assertRegex(
match, expected,
'Expect jsonpath %s to match /%s/, got %s' %
(path, expected, match))
else:
test.assertEqual(expected, match,
'Unable to match %s as %s, got %s' %
(path, expected, match))
|
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] |
https://github.com/cdent/gabbi/blob/73dd8996ef4c7a9b50eb70532f830b71d41a1225/gabbi/handlers/jsonhandler.py#L91-L141
|
||
openstack/cinder
|
23494a6d6c51451688191e1847a458f1d3cdcaa5
|
cinder/volume/drivers/nimble.py
|
python
|
NimbleBaseVolumeDriver.delete_group_snapshot
|
(self, context, group_snapshot, snapshots)
|
return model_update, snapshots_model_update
|
Deletes a group snapshot.
|
Deletes a group snapshot.
|
[
"Deletes",
"a",
"group",
"snapshot",
"."
] |
def delete_group_snapshot(self, context, group_snapshot, snapshots):
"""Deletes a group snapshot."""
if not volume_utils.is_group_a_cg_snapshot_type(group_snapshot):
raise NotImplementedError()
snap_name = group_snapshot.id
model_update = {'status': fields.ConsistencyGroupStatus.DELETED}
snapshots_model_update = []
snapcoll_id = self.APIExecutor.get_snapcoll_id_by_name(snap_name)
try:
self.APIExecutor.snapcoll_delete(snapcoll_id)
for snapshot in snapshots:
snapshots_model_update.append(
{'id': snapshot.id,
'status': fields.SnapshotStatus.DELETED})
except Exception as e:
LOG.error("Error deleting volume group snapshot."
"Error received: %(e)s", {'e': e})
model_update = {
'status': fields.GroupSnapshotStatus.ERROR_DELETING}
return model_update, snapshots_model_update
|
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"group_snapshot",
".",
"id",
"model_update",
"=",
"{",
"'status'",
":",
"fields",
".",
"ConsistencyGroupStatus",
".",
"DELETED",
"}",
"snapshots_model_update",
"=",
"[",
"]",
"snapcoll_id",
"=",
"self",
".",
"APIExecutor",
".",
"get_snapcoll_id_by_name",
"(",
"snap_name",
")",
"try",
":",
"self",
".",
"APIExecutor",
".",
"snapcoll_delete",
"(",
"snapcoll_id",
")",
"for",
"snapshot",
"in",
"snapshots",
":",
"snapshots_model_update",
".",
"append",
"(",
"{",
"'id'",
":",
"snapshot",
".",
"id",
",",
"'status'",
":",
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".",
"SnapshotStatus",
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"DELETED",
"}",
")",
"except",
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"as",
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"LOG",
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"error",
"(",
"\"Error deleting volume group snapshot.\"",
"\"Error received: %(e)s\"",
",",
"{",
"'e'",
":",
"e",
"}",
")",
"model_update",
"=",
"{",
"'status'",
":",
"fields",
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"GroupSnapshotStatus",
".",
"ERROR_DELETING",
"}",
"return",
"model_update",
",",
"snapshots_model_update"
] |
https://github.com/openstack/cinder/blob/23494a6d6c51451688191e1847a458f1d3cdcaa5/cinder/volume/drivers/nimble.py#L901-L920
|
|
ioflo/ioflo
|
177ac656d7c4ff801aebb0d8b401db365a5248ce
|
ioflo/aid/vectoring.py
|
python
|
insideOnly
|
(p, vs)
|
return inside(p, vs, side=False)
|
Returns True if p is strictly inside polygon given by vs, False otherwise.
If p on edge or vertex it is considered as outside
|
Returns True if p is strictly inside polygon given by vs, False otherwise.
If p on edge or vertex it is considered as outside
|
[
"Returns",
"True",
"if",
"p",
"is",
"strictly",
"inside",
"polygon",
"given",
"by",
"vs",
"False",
"otherwise",
".",
"If",
"p",
"on",
"edge",
"or",
"vertex",
"it",
"is",
"considered",
"as",
"outside"
] |
def insideOnly(p, vs):
"""
Returns True if p is strictly inside polygon given by vs, False otherwise.
If p on edge or vertex it is considered as outside
"""
return inside(p, vs, side=False)
|
[
"def",
"insideOnly",
"(",
"p",
",",
"vs",
")",
":",
"return",
"inside",
"(",
"p",
",",
"vs",
",",
"side",
"=",
"False",
")"
] |
https://github.com/ioflo/ioflo/blob/177ac656d7c4ff801aebb0d8b401db365a5248ce/ioflo/aid/vectoring.py#L344-L349
|
|
GoogleCloudPlatform/professional-services
|
0c707aa97437f3d154035ef8548109b7882f71da
|
examples/dlp/cloud_function_example/cloud_function/main.py
|
python
|
_post_scrubbed_message_to_pub_sub
|
(message_topic, scrubbed_message,
log_json)
|
Posts the log json payload with redacted PII to a pub/sub topic.
Args:
message_topic: The pub/sub topic to post the message to.
scrubbed_message: The PII scrubbed message string.
log_json: The original log json.
|
Posts the log json payload with redacted PII to a pub/sub topic.
|
[
"Posts",
"the",
"log",
"json",
"payload",
"with",
"redacted",
"PII",
"to",
"a",
"pub",
"/",
"sub",
"topic",
"."
] |
def _post_scrubbed_message_to_pub_sub(message_topic, scrubbed_message,
log_json):
"""Posts the log json payload with redacted PII to a pub/sub topic.
Args:
message_topic: The pub/sub topic to post the message to.
scrubbed_message: The PII scrubbed message string.
log_json: The original log json.
"""
publisher = pubsub_v1.PublisherClient()
topic_path = publisher.topic_path(_PROJECT_ID, message_topic)
log_json['jsonPayload']['message'] = scrubbed_message
data = json.dumps(log_json).encode('utf-8')
message_future = publisher.publish(topic_path, data=data)
message_future.add_done_callback(_post_scrubbed_message_callback)
|
[
"def",
"_post_scrubbed_message_to_pub_sub",
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"scrubbed_message",
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"log_json",
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"_post_scrubbed_message_callback",
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] |
https://github.com/GoogleCloudPlatform/professional-services/blob/0c707aa97437f3d154035ef8548109b7882f71da/examples/dlp/cloud_function_example/cloud_function/main.py#L125-L140
|
||
ipython/ipython
|
c0abea7a6dfe52c1f74c9d0387d4accadba7cc14
|
IPython/lib/backgroundjobs.py
|
python
|
BackgroundJobManager.remove
|
(self,num)
|
Remove a finished (completed or dead) job.
|
Remove a finished (completed or dead) job.
|
[
"Remove",
"a",
"finished",
"(",
"completed",
"or",
"dead",
")",
"job",
"."
] |
def remove(self,num):
"""Remove a finished (completed or dead) job."""
try:
job = self.all[num]
except KeyError:
error('Job #%s not found' % num)
else:
stat_code = job.stat_code
if stat_code == self._s_running:
error('Job #%s is still running, it can not be removed.' % num)
return
elif stat_code == self._s_completed:
self.completed.remove(job)
elif stat_code == self._s_dead:
self.dead.remove(job)
|
[
"def",
"remove",
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"self",
",",
"num",
")",
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"try",
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"job",
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"%",
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"self",
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"dead",
".",
"remove",
"(",
"job",
")"
] |
https://github.com/ipython/ipython/blob/c0abea7a6dfe52c1f74c9d0387d4accadba7cc14/IPython/lib/backgroundjobs.py#L295-L310
|
||
moinwiki/moin
|
568f223231aadecbd3b21a701ec02271f8d8021d
|
src/moin/macros/MailTo.py
|
python
|
Macro.macro
|
(self, content, arguments, page_url, alternative)
|
return result
|
Invocation: <<MailTo(user AT example DOT org, write me)>>
where 2nd parameter is optional.
|
Invocation: <<MailTo(user AT example DOT org, write me)>>
where 2nd parameter is optional.
|
[
"Invocation",
":",
"<<MailTo",
"(",
"user",
"AT",
"example",
"DOT",
"org",
"write",
"me",
")",
">>",
"where",
"2nd",
"parameter",
"is",
"optional",
"."
] |
def macro(self, content, arguments, page_url, alternative):
"""
Invocation: <<MailTo(user AT example DOT org, write me)>>
where 2nd parameter is optional.
"""
if arguments:
arguments = arguments[0].split(',')
try:
assert len(arguments) > 0 and len(arguments) < 3
email = arguments[0]
assert len(email) >= 5
except (AttributeError, AssertionError):
raise ValueError(_("MailTo: invalid format, try: <<MailTo(user AT example DOT org, write me)>>"))
try:
text = arguments[1]
except IndexError:
text = ''
if flaskg.user.valid:
# decode address and generate mailto: link
email = decodeSpamSafeEmail(email)
result = moin_page.a(attrib={xlink.href: 'mailto:{0}'.format(email)}, children=[text or email])
else:
# unknown user, maybe even a spambot, so just return text as given in macro args
if text:
text += " "
result = moin_page.code(children=[text, "<{0}>".format(email)])
return result
|
[
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"macro",
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"content",
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"page_url",
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"'mailto:{0}'",
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"}",
",",
"children",
"=",
"[",
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"(",
"email",
")",
"]",
")",
"return",
"result"
] |
https://github.com/moinwiki/moin/blob/568f223231aadecbd3b21a701ec02271f8d8021d/src/moin/macros/MailTo.py#L20-L49
|
|
kmpm/nodemcu-uploader
|
6178f40fff2deadd56b5bc474f9b4475ef444b37
|
nodemcu_uploader/uploader.py
|
python
|
Uploader.exec_file
|
(self, path)
|
execute the lines in the local file 'path
|
execute the lines in the local file 'path
|
[
"execute",
"the",
"lines",
"in",
"the",
"local",
"file",
"path"
] |
def exec_file(self, path):
"""execute the lines in the local file 'path'"""
filename = os.path.basename(path)
log.info('Execute %s', filename)
content = from_file(path).replace('\r', '').split('\n')
res = '> '
for line in content:
line = line.rstrip('\n')
retlines = (res + self.__exchange(line)).splitlines()
# Log all but the last line
res = retlines.pop()
for lin in retlines:
log.info(lin)
# last line
log.info(res)
|
[
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"(",
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"# last line",
"log",
".",
"info",
"(",
"res",
")"
] |
https://github.com/kmpm/nodemcu-uploader/blob/6178f40fff2deadd56b5bc474f9b4475ef444b37/nodemcu_uploader/uploader.py#L358-L374
|
||
RobotLocomotion/LabelFusion
|
e4d90bef01552a9e26e8ee37177f92294ce03217
|
modules/labelfusion/registration.py
|
python
|
GlobalRegistration.segmentTable
|
(self, scenePolyData=None, searchRadius=0.3, visualize=True,
thickness=0.01, pointOnTable=None, pointAboveTable=None)
|
return returnData
|
This requires two clicks using measurement panel. One on the table, one above the table on one of the objects. Call them point0, point1. Then we will attempt to fit a plane that passes through point0 with approximate normal point1 - point0
:param scenePolyData:
:param searchRadius:
:return:
|
This requires two clicks using measurement panel. One on the table, one above the table on one of the objects. Call them point0, point1. Then we will attempt to fit a plane that passes through point0 with approximate normal point1 - point0
:param scenePolyData:
:param searchRadius:
:return:
|
[
"This",
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".",
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"the",
"table",
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"table",
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"-",
"point0",
":",
"param",
"scenePolyData",
":",
":",
"param",
"searchRadius",
":",
":",
"return",
":"
] |
def segmentTable(self, scenePolyData=None, searchRadius=0.3, visualize=True,
thickness=0.01, pointOnTable=None, pointAboveTable=None):
"""
This requires two clicks using measurement panel. One on the table, one above the table on one of the objects. Call them point0, point1. Then we will attempt to fit a plane that passes through point0 with approximate normal point1 - point0
:param scenePolyData:
:param searchRadius:
:return:
"""
if scenePolyData is None:
scenePolyData = om.findObjectByName('reconstruction').polyData
if pointOnTable is None:
assert (len(self.measurementPanel.pickPoints) >= 2)
pointOnTable = self.measurementPanel.pickPoints[0]
pointAboveTable = self.measurementPanel.pickPoints[1]
expectedNormal= pointAboveTable - pointOnTable
expectedNormal = expectedNormal/np.linalg.norm(expectedNormal)
polyData, normal = segmentation.applyPlaneFit(scenePolyData, searchOrigin=pointOnTable, searchRadius=searchRadius, expectedNormal=expectedNormal)
# get points above plane
abovePolyData = filterUtils.thresholdPoints(polyData, 'dist_to_plane', [thickness / 2.0, np.inf])
belowPolyData = filterUtils.thresholdPoints(polyData, 'dist_to_plane', [-np.inf, -thickness / 2.0])
self.aboveTablePolyData = abovePolyData
# some debugging visualization
if visualize:
vis.showPolyData(abovePolyData, 'above table segmentation', color=[0, 1, 0],
parent=self.visFolder)
arrowLength = 0.3
headRadius = 0.02
d = DebugData()
d.addArrow(pointOnTable, pointOnTable + arrowLength*expectedNormal,
headRadius=headRadius)
vis.showPolyData(d.getPolyData(), 'expected normal', color=[1, 0, 0],
parent=self.visFolder)
d = DebugData()
d.addArrow(pointOnTable, pointOnTable + arrowLength * normal,
headRadius=headRadius)
vis.showPolyData(d.getPolyData(), 'computed normal', color=[0, 1, 0],
parent=self.visFolder)
returnData = dict()
returnData['abovePolyData'] = abovePolyData
returnData['polyData'] = polyData
returnData['normal'] = normal
returnData['pointOnTable'] = pointOnTable
return returnData
|
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] |
https://github.com/RobotLocomotion/LabelFusion/blob/e4d90bef01552a9e26e8ee37177f92294ce03217/modules/labelfusion/registration.py#L150-L206
|
|
youyuge34/PI-REC
|
9f8f1adff169fda301f3134ac730991484a6b128
|
main.py
|
python
|
load_config_costume
|
(mode, config)
|
return config
|
r"""loads model costume config
Args:
mode (int): 5: draw
mode (int): 6: refinement
|
r"""loads model costume config
|
[
"r",
"loads",
"model",
"costume",
"config"
] |
def load_config_costume(mode, config):
r"""loads model costume config
Args:
mode (int): 5: draw
mode (int): 6: refinement
"""
print('load_config_demo----->')
if mode == 5:
config.MODE = 5
elif mode == 6:
config.MODE = 6
return config
|
[
"def",
"load_config_costume",
"(",
"mode",
",",
"config",
")",
":",
"print",
"(",
"'load_config_demo----->'",
")",
"if",
"mode",
"==",
"5",
":",
"config",
".",
"MODE",
"=",
"5",
"elif",
"mode",
"==",
"6",
":",
"config",
".",
"MODE",
"=",
"6",
"return",
"config"
] |
https://github.com/youyuge34/PI-REC/blob/9f8f1adff169fda301f3134ac730991484a6b128/main.py#L151-L163
|
|
kanzure/pyphantomjs
|
e878516bb10f6ce27302aabb5a5f30247ea261b8
|
pyphantomjs/utils.py
|
python
|
MessageHandler.process
|
(self, msgType, msg)
|
[] |
def process(self, msgType, msg):
now = QDateTime.currentDateTime().toString(Qt.ISODate)
if msgType == QtDebugMsg:
if self.verbose:
print '%s [DEBUG] %s' % (now, msg)
elif msgType == QtWarningMsg:
print >> sys.stderr, '%s [WARNING] %s' % (now, msg)
elif msgType == QtCriticalMsg:
print >> sys.stderr, '%s [CRITICAL] %s' % (now, msg)
elif msgType == QtFatalMsg:
print >> sys.stderr, '%s [FATAL] %s' % (now, msg)
|
[
"def",
"process",
"(",
"self",
",",
"msgType",
",",
"msg",
")",
":",
"now",
"=",
"QDateTime",
".",
"currentDateTime",
"(",
")",
".",
"toString",
"(",
"Qt",
".",
"ISODate",
")",
"if",
"msgType",
"==",
"QtDebugMsg",
":",
"if",
"self",
".",
"verbose",
":",
"print",
"'%s [DEBUG] %s'",
"%",
"(",
"now",
",",
"msg",
")",
"elif",
"msgType",
"==",
"QtWarningMsg",
":",
"print",
">>",
"sys",
".",
"stderr",
",",
"'%s [WARNING] %s'",
"%",
"(",
"now",
",",
"msg",
")",
"elif",
"msgType",
"==",
"QtCriticalMsg",
":",
"print",
">>",
"sys",
".",
"stderr",
",",
"'%s [CRITICAL] %s'",
"%",
"(",
"now",
",",
"msg",
")",
"elif",
"msgType",
"==",
"QtFatalMsg",
":",
"print",
">>",
"sys",
".",
"stderr",
",",
"'%s [FATAL] %s'",
"%",
"(",
"now",
",",
"msg",
")"
] |
https://github.com/kanzure/pyphantomjs/blob/e878516bb10f6ce27302aabb5a5f30247ea261b8/pyphantomjs/utils.py#L95-L106
|
||||
CENSUS/choronzon
|
d702c318e2292a061da57d7ba5f88d4c4b0f5256
|
choronzon.py
|
python
|
Choronzon.fuzz
|
(self)
|
Each time fuzz method is called, it is indicating that a new epoch
has begun. The function picks random couples of chromosomes from the
population and apply to them recombination and mutation algorithms.
Finally, the new (fuzzed) chromosomes are imported to the new
generation.
|
Each time fuzz method is called, it is indicating that a new epoch
has begun. The function picks random couples of chromosomes from the
population and apply to them recombination and mutation algorithms.
Finally, the new (fuzzed) chromosomes are imported to the new
generation.
|
[
"Each",
"time",
"fuzz",
"method",
"is",
"called",
"it",
"is",
"indicating",
"that",
"a",
"new",
"epoch",
"has",
"begun",
".",
"The",
"function",
"picks",
"random",
"couples",
"of",
"chromosomes",
"from",
"the",
"population",
"and",
"apply",
"to",
"them",
"recombination",
"and",
"mutation",
"algorithms",
".",
"Finally",
"the",
"new",
"(",
"fuzzed",
")",
"chromosomes",
"are",
"imported",
"to",
"the",
"new",
"generation",
"."
] |
def fuzz(self):
'''
Each time fuzz method is called, it is indicating that a new epoch
has begun. The function picks random couples of chromosomes from the
population and apply to them recombination and mutation algorithms.
Finally, the new (fuzzed) chromosomes are imported to the new
generation.
'''
self.population.new_epoch()
self.campaign.log('Fuzzing of chromosomes has begun.')
# This is to keep the family tree of the chromosomes
for male, female in self.population.get_couple_from_previous(True):
# assume that the UID is colliding with another's chromosome UID
uid_collision = True
maleclone = male.clone()
femaleclone = female.clone()
# assign new UIDs to the new chromosomes until they are unique
while uid_collision:
if self.population.does_exist(maleclone.uid) == False and \
self.population.does_exist(femaleclone.uid) == False:
uid_collision = False
else:
maleclone.new_uid()
femaleclone.new_uid()
son, daughter = self.strategy.recombine(maleclone, femaleclone)
self.population.add_chromosome(son)
self.population.add_chromosome(daughter)
self.campaign.log('The stage of fuzzing is finished')
if 'KeepGenerations' in self.configuration and \
self.configuration['KeepGenerations']:
gpath = self.campaign.create_directory(
'%s' % self.population.epoch
)
for chromo in self.population.get_all_from_current():
path = os.path.join(
'%s' % gpath,
'%s' % chromo.uid
)
with open(path, 'wb') as fout:
fout.write(chromo.serialize())
|
[
"def",
"fuzz",
"(",
"self",
")",
":",
"self",
".",
"population",
".",
"new_epoch",
"(",
")",
"self",
".",
"campaign",
".",
"log",
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"'Fuzzing of chromosomes has begun.'",
")",
"# This is to keep the family tree of the chromosomes",
"for",
"male",
",",
"female",
"in",
"self",
".",
"population",
".",
"get_couple_from_previous",
"(",
"True",
")",
":",
"# assume that the UID is colliding with another's chromosome UID",
"uid_collision",
"=",
"True",
"maleclone",
"=",
"male",
".",
"clone",
"(",
")",
"femaleclone",
"=",
"female",
".",
"clone",
"(",
")",
"# assign new UIDs to the new chromosomes until they are unique",
"while",
"uid_collision",
":",
"if",
"self",
".",
"population",
".",
"does_exist",
"(",
"maleclone",
".",
"uid",
")",
"==",
"False",
"and",
"self",
".",
"population",
".",
"does_exist",
"(",
"femaleclone",
".",
"uid",
")",
"==",
"False",
":",
"uid_collision",
"=",
"False",
"else",
":",
"maleclone",
".",
"new_uid",
"(",
")",
"femaleclone",
".",
"new_uid",
"(",
")",
"son",
",",
"daughter",
"=",
"self",
".",
"strategy",
".",
"recombine",
"(",
"maleclone",
",",
"femaleclone",
")",
"self",
".",
"population",
".",
"add_chromosome",
"(",
"son",
")",
"self",
".",
"population",
".",
"add_chromosome",
"(",
"daughter",
")",
"self",
".",
"campaign",
".",
"log",
"(",
"'The stage of fuzzing is finished'",
")",
"if",
"'KeepGenerations'",
"in",
"self",
".",
"configuration",
"and",
"self",
".",
"configuration",
"[",
"'KeepGenerations'",
"]",
":",
"gpath",
"=",
"self",
".",
"campaign",
".",
"create_directory",
"(",
"'%s'",
"%",
"self",
".",
"population",
".",
"epoch",
")",
"for",
"chromo",
"in",
"self",
".",
"population",
".",
"get_all_from_current",
"(",
")",
":",
"path",
"=",
"os",
".",
"path",
".",
"join",
"(",
"'%s'",
"%",
"gpath",
",",
"'%s'",
"%",
"chromo",
".",
"uid",
")",
"with",
"open",
"(",
"path",
",",
"'wb'",
")",
"as",
"fout",
":",
"fout",
".",
"write",
"(",
"chromo",
".",
"serialize",
"(",
")",
")"
] |
https://github.com/CENSUS/choronzon/blob/d702c318e2292a061da57d7ba5f88d4c4b0f5256/choronzon.py#L78-L124
|
||
urwid/urwid
|
e2423b5069f51d318ea1ac0f355a0efe5448f7eb
|
docs/examples/real_edit.py
|
python
|
re_tab
|
(s)
|
Return a tabbed string from an expanded one.
|
Return a tabbed string from an expanded one.
|
[
"Return",
"a",
"tabbed",
"string",
"from",
"an",
"expanded",
"one",
"."
] |
def re_tab(s):
"""Return a tabbed string from an expanded one."""
l = []
p = 0
for i in range(8, len(s), 8):
if s[i-2:i] == " ":
# collapse two or more spaces into a tab
l.append(s[p:i].rstrip() + "\t")
p = i
if p == 0:
return s
else:
l.append(s[p:])
return "".join(l)
|
[
"def",
"re_tab",
"(",
"s",
")",
":",
"l",
"=",
"[",
"]",
"p",
"=",
"0",
"for",
"i",
"in",
"range",
"(",
"8",
",",
"len",
"(",
"s",
")",
",",
"8",
")",
":",
"if",
"s",
"[",
"i",
"-",
"2",
":",
"i",
"]",
"==",
"\" \"",
":",
"# collapse two or more spaces into a tab",
"l",
".",
"append",
"(",
"s",
"[",
"p",
":",
"i",
"]",
".",
"rstrip",
"(",
")",
"+",
"\"\\t\"",
")",
"p",
"=",
"i",
"if",
"p",
"==",
"0",
":",
"return",
"s",
"else",
":",
"l",
".",
"append",
"(",
"s",
"[",
"p",
":",
"]",
")",
"return",
"\"\"",
".",
"join",
"(",
"l",
")"
] |
https://github.com/urwid/urwid/blob/e2423b5069f51d318ea1ac0f355a0efe5448f7eb/docs/examples/real_edit.py#L226-L240
|
||
DxCx/plugin.video.9anime
|
34358c2f701e5ddf19d3276926374a16f63f7b6a
|
resources/lib/ui/js2py/es6/babel.py
|
python
|
PyJs_anonymous_2830_
|
(require, module, exports, this, arguments, var=var)
|
[] |
def PyJs_anonymous_2830_(require, module, exports, this, arguments, var=var):
var = Scope({u'this':this, u'require':require, u'exports':exports, u'module':module, u'arguments':arguments}, var)
var.registers([u'_create', u'exports', u'_interopRequireWildcard', u'_index', u'getBindingIdentifiers', u'require', u'module', u'_create2', u'getOuterBindingIdentifiers', u't', u'_interopRequireDefault'])
@Js
def PyJsHoisted__interopRequireDefault_(obj, this, arguments, var=var):
var = Scope({u'this':this, u'obj':obj, u'arguments':arguments}, var)
var.registers([u'obj'])
PyJs_Object_2832_ = Js({u'default':var.get(u'obj')})
return (var.get(u'obj') if (var.get(u'obj') and var.get(u'obj').get(u'__esModule')) else PyJs_Object_2832_)
PyJsHoisted__interopRequireDefault_.func_name = u'_interopRequireDefault'
var.put(u'_interopRequireDefault', PyJsHoisted__interopRequireDefault_)
@Js
def PyJsHoisted_getBindingIdentifiers_(node, duplicates, outerOnly, this, arguments, var=var):
var = Scope({u'node':node, u'duplicates':duplicates, u'this':this, u'arguments':arguments, u'outerOnly':outerOnly}, var)
var.registers([u'node', u'search', u'duplicates', u'outerOnly', u'keys', u'ids', u'i', u'key', u'id', u'_ids'])
var.put(u'search', Js([]).callprop(u'concat', var.get(u'node')))
var.put(u'ids', PyJsComma(Js(0.0),var.get(u'_create2').get(u'default'))(var.get(u"null")))
while var.get(u'search').get(u'length'):
var.put(u'id', var.get(u'search').callprop(u'shift'))
if var.get(u'id').neg():
continue
var.put(u'keys', var.get(u't').get(u'getBindingIdentifiers').get(u'keys').get(var.get(u'id').get(u'type')))
if var.get(u't').callprop(u'isIdentifier', var.get(u'id')):
if var.get(u'duplicates'):
var.put(u'_ids', var.get(u'ids').put(var.get(u'id').get(u'name'), (var.get(u'ids').get(var.get(u'id').get(u'name')) or Js([]))))
var.get(u'_ids').callprop(u'push', var.get(u'id'))
else:
var.get(u'ids').put(var.get(u'id').get(u'name'), var.get(u'id'))
continue
if var.get(u't').callprop(u'isExportDeclaration', var.get(u'id')):
if var.get(u't').callprop(u'isDeclaration', var.get(u'node').get(u'declaration')):
var.get(u'search').callprop(u'push', var.get(u'node').get(u'declaration'))
continue
if var.get(u'outerOnly'):
if var.get(u't').callprop(u'isFunctionDeclaration', var.get(u'id')):
var.get(u'search').callprop(u'push', var.get(u'id').get(u'id'))
continue
if var.get(u't').callprop(u'isFunctionExpression', var.get(u'id')):
continue
if var.get(u'keys'):
#for JS loop
var.put(u'i', Js(0.0))
while (var.get(u'i')<var.get(u'keys').get(u'length')):
try:
var.put(u'key', var.get(u'keys').get(var.get(u'i')))
if var.get(u'id').get(var.get(u'key')):
var.put(u'search', var.get(u'search').callprop(u'concat', var.get(u'id').get(var.get(u'key'))))
finally:
(var.put(u'i',Js(var.get(u'i').to_number())+Js(1))-Js(1))
return var.get(u'ids')
PyJsHoisted_getBindingIdentifiers_.func_name = u'getBindingIdentifiers'
var.put(u'getBindingIdentifiers', PyJsHoisted_getBindingIdentifiers_)
@Js
def PyJsHoisted_getOuterBindingIdentifiers_(node, duplicates, this, arguments, var=var):
var = Scope({u'node':node, u'duplicates':duplicates, u'this':this, u'arguments':arguments}, var)
var.registers([u'node', u'duplicates'])
return var.get(u'getBindingIdentifiers')(var.get(u'node'), var.get(u'duplicates'), var.get(u'true'))
PyJsHoisted_getOuterBindingIdentifiers_.func_name = u'getOuterBindingIdentifiers'
var.put(u'getOuterBindingIdentifiers', PyJsHoisted_getOuterBindingIdentifiers_)
@Js
def PyJsHoisted__interopRequireWildcard_(obj, this, arguments, var=var):
var = Scope({u'this':this, u'obj':obj, u'arguments':arguments}, var)
var.registers([u'obj', u'key', u'newObj'])
if (var.get(u'obj') and var.get(u'obj').get(u'__esModule')):
return var.get(u'obj')
else:
PyJs_Object_2831_ = Js({})
var.put(u'newObj', PyJs_Object_2831_)
if (var.get(u'obj')!=var.get(u"null")):
for PyJsTemp in var.get(u'obj'):
var.put(u'key', PyJsTemp)
if var.get(u'Object').get(u'prototype').get(u'hasOwnProperty').callprop(u'call', var.get(u'obj'), var.get(u'key')):
var.get(u'newObj').put(var.get(u'key'), var.get(u'obj').get(var.get(u'key')))
var.get(u'newObj').put(u'default', var.get(u'obj'))
return var.get(u'newObj')
PyJsHoisted__interopRequireWildcard_.func_name = u'_interopRequireWildcard'
var.put(u'_interopRequireWildcard', PyJsHoisted__interopRequireWildcard_)
Js(u'use strict')
var.get(u'exports').put(u'__esModule', var.get(u'true'))
var.put(u'_create', var.get(u'require')(Js(u'babel-runtime/core-js/object/create')))
var.put(u'_create2', var.get(u'_interopRequireDefault')(var.get(u'_create')))
var.get(u'exports').put(u'getBindingIdentifiers', var.get(u'getBindingIdentifiers'))
var.get(u'exports').put(u'getOuterBindingIdentifiers', var.get(u'getOuterBindingIdentifiers'))
var.put(u'_index', var.get(u'require')(Js(u'./index')))
var.put(u't', var.get(u'_interopRequireWildcard')(var.get(u'_index')))
pass
pass
pass
PyJs_Object_2833_ = Js({u'DeclareClass':Js([Js(u'id')]),u'DeclareFunction':Js([Js(u'id')]),u'DeclareModule':Js([Js(u'id')]),u'DeclareVariable':Js([Js(u'id')]),u'InterfaceDeclaration':Js([Js(u'id')]),u'TypeAlias':Js([Js(u'id')]),u'CatchClause':Js([Js(u'param')]),u'LabeledStatement':Js([Js(u'label')]),u'UnaryExpression':Js([Js(u'argument')]),u'AssignmentExpression':Js([Js(u'left')]),u'ImportSpecifier':Js([Js(u'local')]),u'ImportNamespaceSpecifier':Js([Js(u'local')]),u'ImportDefaultSpecifier':Js([Js(u'local')]),u'ImportDeclaration':Js([Js(u'specifiers')]),u'ExportSpecifier':Js([Js(u'exported')]),u'ExportNamespaceSpecifier':Js([Js(u'exported')]),u'ExportDefaultSpecifier':Js([Js(u'exported')]),u'FunctionDeclaration':Js([Js(u'id'), Js(u'params')]),u'FunctionExpression':Js([Js(u'id'), Js(u'params')]),u'ClassDeclaration':Js([Js(u'id')]),u'ClassExpression':Js([Js(u'id')]),u'RestElement':Js([Js(u'argument')]),u'UpdateExpression':Js([Js(u'argument')]),u'RestProperty':Js([Js(u'argument')]),u'ObjectProperty':Js([Js(u'value')]),u'AssignmentPattern':Js([Js(u'left')]),u'ArrayPattern':Js([Js(u'elements')]),u'ObjectPattern':Js([Js(u'properties')]),u'VariableDeclaration':Js([Js(u'declarations')]),u'VariableDeclarator':Js([Js(u'id')])})
var.get(u'getBindingIdentifiers').put(u'keys', PyJs_Object_2833_)
pass
|
[
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",",
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",",
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",",
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https://github.com/DxCx/plugin.video.9anime/blob/34358c2f701e5ddf19d3276926374a16f63f7b6a/resources/lib/ui/js2py/es6/babel.py#L29394-L29484
|
||||
zyfra/ebonite
|
b01b662c43709d152940f488574d78ff25f89ecf
|
src/ebonite/build/builder/base.py
|
python
|
PythonBuildContext.__init__
|
(self, provider: PythonProvider)
|
[] |
def __init__(self, provider: PythonProvider):
self.provider = provider
|
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"PythonProvider",
")",
":",
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"provider",
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] |
https://github.com/zyfra/ebonite/blob/b01b662c43709d152940f488574d78ff25f89ecf/src/ebonite/build/builder/base.py#L81-L82
|
||||
zedshaw/learn-more-python-the-hard-way-solutions
|
7886c860f69d69739a41d6490b8dc3fa777f227b
|
ex14_dllist/dllist.py
|
python
|
DoubleLinkedList.get
|
(self, index)
|
return None
|
Get the value at index.
|
Get the value at index.
|
[
"Get",
"the",
"value",
"at",
"index",
"."
] |
def get(self, index):
"""Get the value at index."""
# similar code to count, but stop at index and return value or None
node = self.begin
i = 0
while node:
if i == index:
return node.value
else:
i += 1
node = node.next
return None
|
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"i",
"=",
"0",
"while",
"node",
":",
"if",
"i",
"==",
"index",
":",
"return",
"node",
".",
"value",
"else",
":",
"i",
"+=",
"1",
"node",
"=",
"node",
".",
"next",
"return",
"None"
] |
https://github.com/zedshaw/learn-more-python-the-hard-way-solutions/blob/7886c860f69d69739a41d6490b8dc3fa777f227b/ex14_dllist/dllist.py#L137-L148
|
|
google-research/tapas
|
a3e069b50c71f50b12a6e5bb3dad10fb51f6fe68
|
tapas/utils/table_pruning.py
|
python
|
ModelPruningSelector._gather_scores
|
(self, scores,
input_mask)
|
return tf.gather_nd(indices=indexes, params=scores, batch_dims=1)
|
Gather the smaller tensor of scores.
|
Gather the smaller tensor of scores.
|
[
"Gather",
"the",
"smaller",
"tensor",
"of",
"scores",
"."
] |
def _gather_scores(self, scores,
input_mask):
"""Gather the smaller tensor of scores."""
# <int32>[batch_size, max_num_tokens, 1]
indexes = self._get_index_gather(scores=scores, input_mask=input_mask)
# <float32>[batch_size, max_num_tokens]
return tf.gather_nd(indices=indexes, params=scores, batch_dims=1)
|
[
"def",
"_gather_scores",
"(",
"self",
",",
"scores",
",",
"input_mask",
")",
":",
"# <int32>[batch_size, max_num_tokens, 1]",
"indexes",
"=",
"self",
".",
"_get_index_gather",
"(",
"scores",
"=",
"scores",
",",
"input_mask",
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"input_mask",
")",
"# <float32>[batch_size, max_num_tokens]",
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"tf",
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"gather_nd",
"(",
"indices",
"=",
"indexes",
",",
"params",
"=",
"scores",
",",
"batch_dims",
"=",
"1",
")"
] |
https://github.com/google-research/tapas/blob/a3e069b50c71f50b12a6e5bb3dad10fb51f6fe68/tapas/utils/table_pruning.py#L170-L176
|
|
learningequality/ka-lite
|
571918ea668013dcf022286ea85eff1c5333fb8b
|
kalite/packages/bundled/django/forms/widgets.py
|
python
|
Widget.build_attrs
|
(self, extra_attrs=None, **kwargs)
|
return attrs
|
Helper function for building an attribute dictionary.
|
Helper function for building an attribute dictionary.
|
[
"Helper",
"function",
"for",
"building",
"an",
"attribute",
"dictionary",
"."
] |
def build_attrs(self, extra_attrs=None, **kwargs):
"Helper function for building an attribute dictionary."
attrs = dict(self.attrs, **kwargs)
if extra_attrs:
attrs.update(extra_attrs)
return attrs
|
[
"def",
"build_attrs",
"(",
"self",
",",
"extra_attrs",
"=",
"None",
",",
"*",
"*",
"kwargs",
")",
":",
"attrs",
"=",
"dict",
"(",
"self",
".",
"attrs",
",",
"*",
"*",
"kwargs",
")",
"if",
"extra_attrs",
":",
"attrs",
".",
"update",
"(",
"extra_attrs",
")",
"return",
"attrs"
] |
https://github.com/learningequality/ka-lite/blob/571918ea668013dcf022286ea85eff1c5333fb8b/kalite/packages/bundled/django/forms/widgets.py#L197-L202
|
|
buke/GreenOdoo
|
3d8c55d426fb41fdb3f2f5a1533cfe05983ba1df
|
runtime/python/lib/python2.7/site-packages/atom/__init__.py
|
python
|
Contributor.__init__
|
(self, name=None, email=None, uri=None,
extension_elements=None, extension_attributes=None, text=None)
|
Constructor for Contributor
Args:
name: Name
email: Email
uri: Uri
extension_elements: list A list of ExtensionElement instances
extension_attributes: dict A dictionary of attribute value string pairs
text: str The text data in the this element
|
Constructor for Contributor
|
[
"Constructor",
"for",
"Contributor"
] |
def __init__(self, name=None, email=None, uri=None,
extension_elements=None, extension_attributes=None, text=None):
"""Constructor for Contributor
Args:
name: Name
email: Email
uri: Uri
extension_elements: list A list of ExtensionElement instances
extension_attributes: dict A dictionary of attribute value string pairs
text: str The text data in the this element
"""
self.name = name
self.email = email
self.uri = uri
self.extension_elements = extension_elements or []
self.extension_attributes = extension_attributes or {}
self.text = text
|
[
"def",
"__init__",
"(",
"self",
",",
"name",
"=",
"None",
",",
"email",
"=",
"None",
",",
"uri",
"=",
"None",
",",
"extension_elements",
"=",
"None",
",",
"extension_attributes",
"=",
"None",
",",
"text",
"=",
"None",
")",
":",
"self",
".",
"name",
"=",
"name",
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"email",
"=",
"email",
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"uri",
"=",
"uri",
"self",
".",
"extension_elements",
"=",
"extension_elements",
"or",
"[",
"]",
"self",
".",
"extension_attributes",
"=",
"extension_attributes",
"or",
"{",
"}",
"self",
".",
"text",
"=",
"text"
] |
https://github.com/buke/GreenOdoo/blob/3d8c55d426fb41fdb3f2f5a1533cfe05983ba1df/runtime/python/lib/python2.7/site-packages/atom/__init__.py#L547-L565
|
||
JiYou/openstack
|
8607dd488bde0905044b303eb6e52bdea6806923
|
packages/source/nova/nova/virt/libvirt/utils.py
|
python
|
delete_snapshot
|
(disk_path, snapshot_name)
|
Create a snapshot in a disk image
:param disk_path: Path to disk image
:param snapshot_name: Name of snapshot in disk image
|
Create a snapshot in a disk image
|
[
"Create",
"a",
"snapshot",
"in",
"a",
"disk",
"image"
] |
def delete_snapshot(disk_path, snapshot_name):
"""Create a snapshot in a disk image
:param disk_path: Path to disk image
:param snapshot_name: Name of snapshot in disk image
"""
qemu_img_cmd = ('qemu-img', 'snapshot', '-d', snapshot_name, disk_path)
# NOTE(vish): libvirt changes ownership of images
execute(*qemu_img_cmd, run_as_root=True)
|
[
"def",
"delete_snapshot",
"(",
"disk_path",
",",
"snapshot_name",
")",
":",
"qemu_img_cmd",
"=",
"(",
"'qemu-img'",
",",
"'snapshot'",
",",
"'-d'",
",",
"snapshot_name",
",",
"disk_path",
")",
"# NOTE(vish): libvirt changes ownership of images",
"execute",
"(",
"*",
"qemu_img_cmd",
",",
"run_as_root",
"=",
"True",
")"
] |
https://github.com/JiYou/openstack/blob/8607dd488bde0905044b303eb6e52bdea6806923/packages/source/nova/nova/virt/libvirt/utils.py#L474-L482
|
||
pengming617/bert_classification
|
c155e73ee9272aa61589116aebd762204c3e4c83
|
run_classifier.py
|
python
|
convert_examples_to_features
|
(examples, label_list, max_seq_length,
tokenizer)
|
return features
|
Convert a set of `InputExample`s to a list of `InputFeatures`.
|
Convert a set of `InputExample`s to a list of `InputFeatures`.
|
[
"Convert",
"a",
"set",
"of",
"InputExample",
"s",
"to",
"a",
"list",
"of",
"InputFeatures",
"."
] |
def convert_examples_to_features(examples, label_list, max_seq_length,
tokenizer):
"""Convert a set of `InputExample`s to a list of `InputFeatures`."""
features = []
for (ex_index, example) in enumerate(examples):
if ex_index % 10000 == 0:
tf.logging.info("Writing example %d of %d" % (ex_index, len(examples)))
feature = convert_single_example(ex_index, example, label_list,
max_seq_length, tokenizer)
features.append(feature)
return features
|
[
"def",
"convert_examples_to_features",
"(",
"examples",
",",
"label_list",
",",
"max_seq_length",
",",
"tokenizer",
")",
":",
"features",
"=",
"[",
"]",
"for",
"(",
"ex_index",
",",
"example",
")",
"in",
"enumerate",
"(",
"examples",
")",
":",
"if",
"ex_index",
"%",
"10000",
"==",
"0",
":",
"tf",
".",
"logging",
".",
"info",
"(",
"\"Writing example %d of %d\"",
"%",
"(",
"ex_index",
",",
"len",
"(",
"examples",
")",
")",
")",
"feature",
"=",
"convert_single_example",
"(",
"ex_index",
",",
"example",
",",
"label_list",
",",
"max_seq_length",
",",
"tokenizer",
")",
"features",
".",
"append",
"(",
"feature",
")",
"return",
"features"
] |
https://github.com/pengming617/bert_classification/blob/c155e73ee9272aa61589116aebd762204c3e4c83/run_classifier.py#L905-L918
|
|
gramps-project/gramps
|
04d4651a43eb210192f40a9f8c2bad8ee8fa3753
|
gramps/gen/relationship.py
|
python
|
RelationshipCalculator._get_parent_unknown
|
(self, level, step='', inlaw='')
|
Internal english method to create relation string
|
Internal english method to create relation string
|
[
"Internal",
"english",
"method",
"to",
"create",
"relation",
"string"
] |
def _get_parent_unknown(self, level, step='', inlaw=''):
"""
Internal english method to create relation string
"""
if level < len(_LEVEL_NAME):
return _LEVEL_NAME[level] + ' ' + '%sancestor%s' % (step, inlaw)
else:
return "distant %sancestor%s (%d generations)" % (step, inlaw,
level)
|
[
"def",
"_get_parent_unknown",
"(",
"self",
",",
"level",
",",
"step",
"=",
"''",
",",
"inlaw",
"=",
"''",
")",
":",
"if",
"level",
"<",
"len",
"(",
"_LEVEL_NAME",
")",
":",
"return",
"_LEVEL_NAME",
"[",
"level",
"]",
"+",
"' '",
"+",
"'%sancestor%s'",
"%",
"(",
"step",
",",
"inlaw",
")",
"else",
":",
"return",
"\"distant %sancestor%s (%d generations)\"",
"%",
"(",
"step",
",",
"inlaw",
",",
"level",
")"
] |
https://github.com/gramps-project/gramps/blob/04d4651a43eb210192f40a9f8c2bad8ee8fa3753/gramps/gen/relationship.py#L921-L929
|
||
openshift/openshift-tools
|
1188778e728a6e4781acf728123e5b356380fe6f
|
ansible/roles/lib_oa_openshift/library/oc_image.py
|
python
|
Utils.cleanup
|
(files)
|
Clean up on exit
|
Clean up on exit
|
[
"Clean",
"up",
"on",
"exit"
] |
def cleanup(files):
'''Clean up on exit '''
for sfile in files:
if os.path.exists(sfile):
if os.path.isdir(sfile):
shutil.rmtree(sfile)
elif os.path.isfile(sfile):
os.remove(sfile)
|
[
"def",
"cleanup",
"(",
"files",
")",
":",
"for",
"sfile",
"in",
"files",
":",
"if",
"os",
".",
"path",
".",
"exists",
"(",
"sfile",
")",
":",
"if",
"os",
".",
"path",
".",
"isdir",
"(",
"sfile",
")",
":",
"shutil",
".",
"rmtree",
"(",
"sfile",
")",
"elif",
"os",
".",
"path",
".",
"isfile",
"(",
"sfile",
")",
":",
"os",
".",
"remove",
"(",
"sfile",
")"
] |
https://github.com/openshift/openshift-tools/blob/1188778e728a6e4781acf728123e5b356380fe6f/ansible/roles/lib_oa_openshift/library/oc_image.py#L1228-L1235
|
||
kubernetes-client/python
|
47b9da9de2d02b2b7a34fbe05afb44afd130d73a
|
kubernetes/client/models/v1_csi_volume_source.py
|
python
|
V1CSIVolumeSource.__repr__
|
(self)
|
return self.to_str()
|
For `print` and `pprint`
|
For `print` and `pprint`
|
[
"For",
"print",
"and",
"pprint"
] |
def __repr__(self):
"""For `print` and `pprint`"""
return self.to_str()
|
[
"def",
"__repr__",
"(",
"self",
")",
":",
"return",
"self",
".",
"to_str",
"(",
")"
] |
https://github.com/kubernetes-client/python/blob/47b9da9de2d02b2b7a34fbe05afb44afd130d73a/kubernetes/client/models/v1_csi_volume_source.py#L217-L219
|
|
pyjs/pyjs
|
6c4a3d3a67300cd5df7f95a67ca9dcdc06950523
|
pgen/tokenize.py
|
python
|
tokenize
|
(readline, tokeneater=printtoken)
|
The tokenize() function accepts two parameters: one representing the
input stream, and one providing an output mechanism for tokenize().
The first parameter, readline, must be a callable object which provides
the same interface as the readline() method of built-in file objects.
Each call to the function should return one line of input as a string.
The second parameter, tokeneater, must also be a callable object. It is
called once for each token, with five arguments, corresponding to the
tuples generated by generate_tokens().
|
The tokenize() function accepts two parameters: one representing the
input stream, and one providing an output mechanism for tokenize().
|
[
"The",
"tokenize",
"()",
"function",
"accepts",
"two",
"parameters",
":",
"one",
"representing",
"the",
"input",
"stream",
"and",
"one",
"providing",
"an",
"output",
"mechanism",
"for",
"tokenize",
"()",
"."
] |
def tokenize(readline, tokeneater=printtoken):
"""
The tokenize() function accepts two parameters: one representing the
input stream, and one providing an output mechanism for tokenize().
The first parameter, readline, must be a callable object which provides
the same interface as the readline() method of built-in file objects.
Each call to the function should return one line of input as a string.
The second parameter, tokeneater, must also be a callable object. It is
called once for each token, with five arguments, corresponding to the
tuples generated by generate_tokens().
"""
try:
tokenize_loop(readline, tokeneater)
except StopTokenizing:
pass
|
[
"def",
"tokenize",
"(",
"readline",
",",
"tokeneater",
"=",
"printtoken",
")",
":",
"try",
":",
"tokenize_loop",
"(",
"readline",
",",
"tokeneater",
")",
"except",
"StopTokenizing",
":",
"pass"
] |
https://github.com/pyjs/pyjs/blob/6c4a3d3a67300cd5df7f95a67ca9dcdc06950523/pgen/tokenize.py#L152-L168
|
||
bardiadoosti/HOPE
|
24f99bb6c4f1d3e185e8988179347dde5c37f42c
|
models/resnet.py
|
python
|
resnet18
|
(pretrained=False, num_classes=1000, **kwargs)
|
return model
|
Constructs a ResNet-18 model.
Args:
pretrained (bool): If True, returns a model pre-trained on ImageNet
|
Constructs a ResNet-18 model.
Args:
pretrained (bool): If True, returns a model pre-trained on ImageNet
|
[
"Constructs",
"a",
"ResNet",
"-",
"18",
"model",
".",
"Args",
":",
"pretrained",
"(",
"bool",
")",
":",
"If",
"True",
"returns",
"a",
"model",
"pre",
"-",
"trained",
"on",
"ImageNet"
] |
def resnet18(pretrained=False, num_classes=1000, **kwargs):
"""Constructs a ResNet-18 model.
Args:
pretrained (bool): If True, returns a model pre-trained on ImageNet
"""
model = ResNet(BasicBlock, [2, 2, 2, 2], num_classes=1000, **kwargs)
if pretrained:
model.load_state_dict(model_zoo.load_url(model_urls['resnet18']))
num_ftrs = model.fc.in_features
model.fc = nn.Linear(num_ftrs, num_classes)
return model
|
[
"def",
"resnet18",
"(",
"pretrained",
"=",
"False",
",",
"num_classes",
"=",
"1000",
",",
"*",
"*",
"kwargs",
")",
":",
"model",
"=",
"ResNet",
"(",
"BasicBlock",
",",
"[",
"2",
",",
"2",
",",
"2",
",",
"2",
"]",
",",
"num_classes",
"=",
"1000",
",",
"*",
"*",
"kwargs",
")",
"if",
"pretrained",
":",
"model",
".",
"load_state_dict",
"(",
"model_zoo",
".",
"load_url",
"(",
"model_urls",
"[",
"'resnet18'",
"]",
")",
")",
"num_ftrs",
"=",
"model",
".",
"fc",
".",
"in_features",
"model",
".",
"fc",
"=",
"nn",
".",
"Linear",
"(",
"num_ftrs",
",",
"num_classes",
")",
"return",
"model"
] |
https://github.com/bardiadoosti/HOPE/blob/24f99bb6c4f1d3e185e8988179347dde5c37f42c/models/resnet.py#L222-L232
|
|
plotly/plotly.py
|
cfad7862594b35965c0e000813bd7805e8494a5b
|
packages/python/plotly/plotly/graph_objs/heatmap/_colorbar.py
|
python
|
ColorBar.outlinecolor
|
(self)
|
return self["outlinecolor"]
|
Sets the axis line color.
The 'outlinecolor' property is a color and may be specified as:
- A hex string (e.g. '#ff0000')
- An rgb/rgba string (e.g. 'rgb(255,0,0)')
- An hsl/hsla string (e.g. 'hsl(0,100%,50%)')
- An hsv/hsva string (e.g. 'hsv(0,100%,100%)')
- A named CSS color:
aliceblue, antiquewhite, aqua, aquamarine, azure,
beige, bisque, black, blanchedalmond, blue,
blueviolet, brown, burlywood, cadetblue,
chartreuse, chocolate, coral, cornflowerblue,
cornsilk, crimson, cyan, darkblue, darkcyan,
darkgoldenrod, darkgray, darkgrey, darkgreen,
darkkhaki, darkmagenta, darkolivegreen, darkorange,
darkorchid, darkred, darksalmon, darkseagreen,
darkslateblue, darkslategray, darkslategrey,
darkturquoise, darkviolet, deeppink, deepskyblue,
dimgray, dimgrey, dodgerblue, firebrick,
floralwhite, forestgreen, fuchsia, gainsboro,
ghostwhite, gold, goldenrod, gray, grey, green,
greenyellow, honeydew, hotpink, indianred, indigo,
ivory, khaki, lavender, lavenderblush, lawngreen,
lemonchiffon, lightblue, lightcoral, lightcyan,
lightgoldenrodyellow, lightgray, lightgrey,
lightgreen, lightpink, lightsalmon, lightseagreen,
lightskyblue, lightslategray, lightslategrey,
lightsteelblue, lightyellow, lime, limegreen,
linen, magenta, maroon, mediumaquamarine,
mediumblue, mediumorchid, mediumpurple,
mediumseagreen, mediumslateblue, mediumspringgreen,
mediumturquoise, mediumvioletred, midnightblue,
mintcream, mistyrose, moccasin, navajowhite, navy,
oldlace, olive, olivedrab, orange, orangered,
orchid, palegoldenrod, palegreen, paleturquoise,
palevioletred, papayawhip, peachpuff, peru, pink,
plum, powderblue, purple, red, rosybrown,
royalblue, rebeccapurple, saddlebrown, salmon,
sandybrown, seagreen, seashell, sienna, silver,
skyblue, slateblue, slategray, slategrey, snow,
springgreen, steelblue, tan, teal, thistle, tomato,
turquoise, violet, wheat, white, whitesmoke,
yellow, yellowgreen
Returns
-------
str
|
Sets the axis line color.
The 'outlinecolor' property is a color and may be specified as:
- A hex string (e.g. '#ff0000')
- An rgb/rgba string (e.g. 'rgb(255,0,0)')
- An hsl/hsla string (e.g. 'hsl(0,100%,50%)')
- An hsv/hsva string (e.g. 'hsv(0,100%,100%)')
- A named CSS color:
aliceblue, antiquewhite, aqua, aquamarine, azure,
beige, bisque, black, blanchedalmond, blue,
blueviolet, brown, burlywood, cadetblue,
chartreuse, chocolate, coral, cornflowerblue,
cornsilk, crimson, cyan, darkblue, darkcyan,
darkgoldenrod, darkgray, darkgrey, darkgreen,
darkkhaki, darkmagenta, darkolivegreen, darkorange,
darkorchid, darkred, darksalmon, darkseagreen,
darkslateblue, darkslategray, darkslategrey,
darkturquoise, darkviolet, deeppink, deepskyblue,
dimgray, dimgrey, dodgerblue, firebrick,
floralwhite, forestgreen, fuchsia, gainsboro,
ghostwhite, gold, goldenrod, gray, grey, green,
greenyellow, honeydew, hotpink, indianred, indigo,
ivory, khaki, lavender, lavenderblush, lawngreen,
lemonchiffon, lightblue, lightcoral, lightcyan,
lightgoldenrodyellow, lightgray, lightgrey,
lightgreen, lightpink, lightsalmon, lightseagreen,
lightskyblue, lightslategray, lightslategrey,
lightsteelblue, lightyellow, lime, limegreen,
linen, magenta, maroon, mediumaquamarine,
mediumblue, mediumorchid, mediumpurple,
mediumseagreen, mediumslateblue, mediumspringgreen,
mediumturquoise, mediumvioletred, midnightblue,
mintcream, mistyrose, moccasin, navajowhite, navy,
oldlace, olive, olivedrab, orange, orangered,
orchid, palegoldenrod, palegreen, paleturquoise,
palevioletred, papayawhip, peachpuff, peru, pink,
plum, powderblue, purple, red, rosybrown,
royalblue, rebeccapurple, saddlebrown, salmon,
sandybrown, seagreen, seashell, sienna, silver,
skyblue, slateblue, slategray, slategrey, snow,
springgreen, steelblue, tan, teal, thistle, tomato,
turquoise, violet, wheat, white, whitesmoke,
yellow, yellowgreen
|
[
"Sets",
"the",
"axis",
"line",
"color",
".",
"The",
"outlinecolor",
"property",
"is",
"a",
"color",
"and",
"may",
"be",
"specified",
"as",
":",
"-",
"A",
"hex",
"string",
"(",
"e",
".",
"g",
".",
"#ff0000",
")",
"-",
"An",
"rgb",
"/",
"rgba",
"string",
"(",
"e",
".",
"g",
".",
"rgb",
"(",
"255",
"0",
"0",
")",
")",
"-",
"An",
"hsl",
"/",
"hsla",
"string",
"(",
"e",
".",
"g",
".",
"hsl",
"(",
"0",
"100%",
"50%",
")",
")",
"-",
"An",
"hsv",
"/",
"hsva",
"string",
"(",
"e",
".",
"g",
".",
"hsv",
"(",
"0",
"100%",
"100%",
")",
")",
"-",
"A",
"named",
"CSS",
"color",
":",
"aliceblue",
"antiquewhite",
"aqua",
"aquamarine",
"azure",
"beige",
"bisque",
"black",
"blanchedalmond",
"blue",
"blueviolet",
"brown",
"burlywood",
"cadetblue",
"chartreuse",
"chocolate",
"coral",
"cornflowerblue",
"cornsilk",
"crimson",
"cyan",
"darkblue",
"darkcyan",
"darkgoldenrod",
"darkgray",
"darkgrey",
"darkgreen",
"darkkhaki",
"darkmagenta",
"darkolivegreen",
"darkorange",
"darkorchid",
"darkred",
"darksalmon",
"darkseagreen",
"darkslateblue",
"darkslategray",
"darkslategrey",
"darkturquoise",
"darkviolet",
"deeppink",
"deepskyblue",
"dimgray",
"dimgrey",
"dodgerblue",
"firebrick",
"floralwhite",
"forestgreen",
"fuchsia",
"gainsboro",
"ghostwhite",
"gold",
"goldenrod",
"gray",
"grey",
"green",
"greenyellow",
"honeydew",
"hotpink",
"indianred",
"indigo",
"ivory",
"khaki",
"lavender",
"lavenderblush",
"lawngreen",
"lemonchiffon",
"lightblue",
"lightcoral",
"lightcyan",
"lightgoldenrodyellow",
"lightgray",
"lightgrey",
"lightgreen",
"lightpink",
"lightsalmon",
"lightseagreen",
"lightskyblue",
"lightslategray",
"lightslategrey",
"lightsteelblue",
"lightyellow",
"lime",
"limegreen",
"linen",
"magenta",
"maroon",
"mediumaquamarine",
"mediumblue",
"mediumorchid",
"mediumpurple",
"mediumseagreen",
"mediumslateblue",
"mediumspringgreen",
"mediumturquoise",
"mediumvioletred",
"midnightblue",
"mintcream",
"mistyrose",
"moccasin",
"navajowhite",
"navy",
"oldlace",
"olive",
"olivedrab",
"orange",
"orangered",
"orchid",
"palegoldenrod",
"palegreen",
"paleturquoise",
"palevioletred",
"papayawhip",
"peachpuff",
"peru",
"pink",
"plum",
"powderblue",
"purple",
"red",
"rosybrown",
"royalblue",
"rebeccapurple",
"saddlebrown",
"salmon",
"sandybrown",
"seagreen",
"seashell",
"sienna",
"silver",
"skyblue",
"slateblue",
"slategray",
"slategrey",
"snow",
"springgreen",
"steelblue",
"tan",
"teal",
"thistle",
"tomato",
"turquoise",
"violet",
"wheat",
"white",
"whitesmoke",
"yellow",
"yellowgreen"
] |
def outlinecolor(self):
"""
Sets the axis line color.
The 'outlinecolor' property is a color and may be specified as:
- A hex string (e.g. '#ff0000')
- An rgb/rgba string (e.g. 'rgb(255,0,0)')
- An hsl/hsla string (e.g. 'hsl(0,100%,50%)')
- An hsv/hsva string (e.g. 'hsv(0,100%,100%)')
- A named CSS color:
aliceblue, antiquewhite, aqua, aquamarine, azure,
beige, bisque, black, blanchedalmond, blue,
blueviolet, brown, burlywood, cadetblue,
chartreuse, chocolate, coral, cornflowerblue,
cornsilk, crimson, cyan, darkblue, darkcyan,
darkgoldenrod, darkgray, darkgrey, darkgreen,
darkkhaki, darkmagenta, darkolivegreen, darkorange,
darkorchid, darkred, darksalmon, darkseagreen,
darkslateblue, darkslategray, darkslategrey,
darkturquoise, darkviolet, deeppink, deepskyblue,
dimgray, dimgrey, dodgerblue, firebrick,
floralwhite, forestgreen, fuchsia, gainsboro,
ghostwhite, gold, goldenrod, gray, grey, green,
greenyellow, honeydew, hotpink, indianred, indigo,
ivory, khaki, lavender, lavenderblush, lawngreen,
lemonchiffon, lightblue, lightcoral, lightcyan,
lightgoldenrodyellow, lightgray, lightgrey,
lightgreen, lightpink, lightsalmon, lightseagreen,
lightskyblue, lightslategray, lightslategrey,
lightsteelblue, lightyellow, lime, limegreen,
linen, magenta, maroon, mediumaquamarine,
mediumblue, mediumorchid, mediumpurple,
mediumseagreen, mediumslateblue, mediumspringgreen,
mediumturquoise, mediumvioletred, midnightblue,
mintcream, mistyrose, moccasin, navajowhite, navy,
oldlace, olive, olivedrab, orange, orangered,
orchid, palegoldenrod, palegreen, paleturquoise,
palevioletred, papayawhip, peachpuff, peru, pink,
plum, powderblue, purple, red, rosybrown,
royalblue, rebeccapurple, saddlebrown, salmon,
sandybrown, seagreen, seashell, sienna, silver,
skyblue, slateblue, slategray, slategrey, snow,
springgreen, steelblue, tan, teal, thistle, tomato,
turquoise, violet, wheat, white, whitesmoke,
yellow, yellowgreen
Returns
-------
str
"""
return self["outlinecolor"]
|
[
"def",
"outlinecolor",
"(",
"self",
")",
":",
"return",
"self",
"[",
"\"outlinecolor\"",
"]"
] |
https://github.com/plotly/plotly.py/blob/cfad7862594b35965c0e000813bd7805e8494a5b/packages/python/plotly/plotly/graph_objs/heatmap/_colorbar.py#L376-L426
|
|
tspurway/hustle
|
e62bf1269b446ea6fae23bc5698f845a2f3247c7
|
hustle/core/pipeline.py
|
python
|
_aggregate_fast
|
(inp, label_fn, ffuncs, ghfuncs, deffuncs)
|
Fast channel for executing aggregate function, would be used if
all columns in project are aggregations
|
Fast channel for executing aggregate function, would be used if
all columns in project are aggregations
|
[
"Fast",
"channel",
"for",
"executing",
"aggregate",
"function",
"would",
"be",
"used",
"if",
"all",
"columns",
"in",
"project",
"are",
"aggregations"
] |
def _aggregate_fast(inp, label_fn, ffuncs, ghfuncs, deffuncs):
"""
Fast channel for executing aggregate function, would be used if
all columns in project are aggregations
"""
accums = [default() for default in deffuncs]
for record, _ in inp:
try:
accums = [f(a, v) for f, a, v in zip(ffuncs, accums, record)]
except Exception as e:
print e
print "YEEHEQW: f=%s a=%s r=%s" % (ffuncs, accums, record)
import traceback
print traceback.format_exc(15)
raise e
key = tuple(h(a) for h, a in zip(ghfuncs, accums))
yield 0, key
|
[
"def",
"_aggregate_fast",
"(",
"inp",
",",
"label_fn",
",",
"ffuncs",
",",
"ghfuncs",
",",
"deffuncs",
")",
":",
"accums",
"=",
"[",
"default",
"(",
")",
"for",
"default",
"in",
"deffuncs",
"]",
"for",
"record",
",",
"_",
"in",
"inp",
":",
"try",
":",
"accums",
"=",
"[",
"f",
"(",
"a",
",",
"v",
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"for",
"f",
",",
"a",
",",
"v",
"in",
"zip",
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"ffuncs",
",",
"accums",
",",
"record",
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"]",
"except",
"Exception",
"as",
"e",
":",
"print",
"e",
"print",
"\"YEEHEQW: f=%s a=%s r=%s\"",
"%",
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"ffuncs",
",",
"accums",
",",
"record",
")",
"import",
"traceback",
"print",
"traceback",
".",
"format_exc",
"(",
"15",
")",
"raise",
"e",
"key",
"=",
"tuple",
"(",
"h",
"(",
"a",
")",
"for",
"h",
",",
"a",
"in",
"zip",
"(",
"ghfuncs",
",",
"accums",
")",
")",
"yield",
"0",
",",
"key"
] |
https://github.com/tspurway/hustle/blob/e62bf1269b446ea6fae23bc5698f845a2f3247c7/hustle/core/pipeline.py#L480-L497
|
||
pulp/pulp
|
a0a28d804f997b6f81c391378aff2e4c90183df9
|
client_admin/pulp/client/admin/tasks.py
|
python
|
AllTasksSection.retrieve_tasks
|
(self, **kwargs)
|
return tasks
|
:return: list of pulp.bindings.responses.Task instances
:rtype: list
|
:return: list of pulp.bindings.responses.Task instances
:rtype: list
|
[
":",
"return",
":",
"list",
"of",
"pulp",
".",
"bindings",
".",
"responses",
".",
"Task",
"instances",
":",
"rtype",
":",
"list"
] |
def retrieve_tasks(self, **kwargs):
"""
:return: list of pulp.bindings.responses.Task instances
:rtype: list
"""
if kwargs.get(self.all_flag.keyword):
tasks = self.context.server.tasks_search.search(fields=self.FIELDS)
elif kwargs.get(self.state_option.keyword):
states = kwargs[self.state_option.keyword]
# This is a temorary fix(because of backward incompatible reasons)
# until #1028 and #1041 are fixed.
self.translate_state_discrepancy(states)
tasks = self.context.server.tasks_search.search(
filters={'state': {'$in': states}, 'group_id': None}, fields=self.FIELDS)
else:
tasks = self.context.server.tasks_search.search(
filters={'state': {'$in': ['running', 'waiting']}, 'group_id': None},
fields=self.FIELDS)
return tasks
|
[
"def",
"retrieve_tasks",
"(",
"self",
",",
"*",
"*",
"kwargs",
")",
":",
"if",
"kwargs",
".",
"get",
"(",
"self",
".",
"all_flag",
".",
"keyword",
")",
":",
"tasks",
"=",
"self",
".",
"context",
".",
"server",
".",
"tasks_search",
".",
"search",
"(",
"fields",
"=",
"self",
".",
"FIELDS",
")",
"elif",
"kwargs",
".",
"get",
"(",
"self",
".",
"state_option",
".",
"keyword",
")",
":",
"states",
"=",
"kwargs",
"[",
"self",
".",
"state_option",
".",
"keyword",
"]",
"# This is a temorary fix(because of backward incompatible reasons)",
"# until #1028 and #1041 are fixed.",
"self",
".",
"translate_state_discrepancy",
"(",
"states",
")",
"tasks",
"=",
"self",
".",
"context",
".",
"server",
".",
"tasks_search",
".",
"search",
"(",
"filters",
"=",
"{",
"'state'",
":",
"{",
"'$in'",
":",
"states",
"}",
",",
"'group_id'",
":",
"None",
"}",
",",
"fields",
"=",
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"FIELDS",
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"else",
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"tasks",
"=",
"self",
".",
"context",
".",
"server",
".",
"tasks_search",
".",
"search",
"(",
"filters",
"=",
"{",
"'state'",
":",
"{",
"'$in'",
":",
"[",
"'running'",
",",
"'waiting'",
"]",
"}",
",",
"'group_id'",
":",
"None",
"}",
",",
"fields",
"=",
"self",
".",
"FIELDS",
")",
"return",
"tasks"
] |
https://github.com/pulp/pulp/blob/a0a28d804f997b6f81c391378aff2e4c90183df9/client_admin/pulp/client/admin/tasks.py#L280-L299
|
|
ajinabraham/OWASP-Xenotix-XSS-Exploit-Framework
|
cb692f527e4e819b6c228187c5702d990a180043
|
external/Scripting Engine/Xenotix Python Scripting Engine/Lib/random.py
|
python
|
Random.choice
|
(self, seq)
|
return seq[int(self.random() * len(seq))]
|
Choose a random element from a non-empty sequence.
|
Choose a random element from a non-empty sequence.
|
[
"Choose",
"a",
"random",
"element",
"from",
"a",
"non",
"-",
"empty",
"sequence",
"."
] |
def choice(self, seq):
"""Choose a random element from a non-empty sequence."""
return seq[int(self.random() * len(seq))]
|
[
"def",
"choice",
"(",
"self",
",",
"seq",
")",
":",
"return",
"seq",
"[",
"int",
"(",
"self",
".",
"random",
"(",
")",
"*",
"len",
"(",
"seq",
")",
")",
"]"
] |
https://github.com/ajinabraham/OWASP-Xenotix-XSS-Exploit-Framework/blob/cb692f527e4e819b6c228187c5702d990a180043/external/Scripting Engine/Xenotix Python Scripting Engine/Lib/random.py#L272-L274
|
|
log2timeline/dfvfs
|
4ca7bf06b15cdc000297a7122a065f0ca71de544
|
dfvfs/volume/volume_system.py
|
python
|
Volume.GetAttribute
|
(self, identifier)
|
return self._attributes[identifier]
|
Retrieves a specific attribute.
Args:
identifier (str): identifier of the attribute within the volume.
Returns:
VolumeAttribute: volume attribute or None if not available.
|
Retrieves a specific attribute.
|
[
"Retrieves",
"a",
"specific",
"attribute",
"."
] |
def GetAttribute(self, identifier):
"""Retrieves a specific attribute.
Args:
identifier (str): identifier of the attribute within the volume.
Returns:
VolumeAttribute: volume attribute or None if not available.
"""
if not self._is_parsed:
self._Parse()
self._is_parsed = True
if identifier not in self._attributes:
return None
return self._attributes[identifier]
|
[
"def",
"GetAttribute",
"(",
"self",
",",
"identifier",
")",
":",
"if",
"not",
"self",
".",
"_is_parsed",
":",
"self",
".",
"_Parse",
"(",
")",
"self",
".",
"_is_parsed",
"=",
"True",
"if",
"identifier",
"not",
"in",
"self",
".",
"_attributes",
":",
"return",
"None",
"return",
"self",
".",
"_attributes",
"[",
"identifier",
"]"
] |
https://github.com/log2timeline/dfvfs/blob/4ca7bf06b15cdc000297a7122a065f0ca71de544/dfvfs/volume/volume_system.py#L117-L133
|
|
superfish9/hackcdn
|
eb164946aad36c3781d73566bdf170b2b1411f0d
|
thirdparty/IPy/IPy.py
|
python
|
_count0Bits
|
(num)
|
return ret
|
Find the highest bit set to 0 in an integer.
|
Find the highest bit set to 0 in an integer.
|
[
"Find",
"the",
"highest",
"bit",
"set",
"to",
"0",
"in",
"an",
"integer",
"."
] |
def _count0Bits(num):
"""Find the highest bit set to 0 in an integer."""
# this could be so easy if _count1Bits(~int(num)) would work as excepted
num = int(num)
if num < 0:
raise ValueError("Only positive Numbers please: %s" % (num))
ret = 0
while num > 0:
if num & 1 == 1:
break
num = num >> 1
ret += 1
return ret
|
[
"def",
"_count0Bits",
"(",
"num",
")",
":",
"# this could be so easy if _count1Bits(~int(num)) would work as excepted",
"num",
"=",
"int",
"(",
"num",
")",
"if",
"num",
"<",
"0",
":",
"raise",
"ValueError",
"(",
"\"Only positive Numbers please: %s\"",
"%",
"(",
"num",
")",
")",
"ret",
"=",
"0",
"while",
"num",
">",
"0",
":",
"if",
"num",
"&",
"1",
"==",
"1",
":",
"break",
"num",
"=",
"num",
">>",
"1",
"ret",
"+=",
"1",
"return",
"ret"
] |
https://github.com/superfish9/hackcdn/blob/eb164946aad36c3781d73566bdf170b2b1411f0d/thirdparty/IPy/IPy.py#L1486-L1499
|
|
OpenMDAO/OpenMDAO-Framework
|
f2e37b7de3edeaaeb2d251b375917adec059db9b
|
openmdao.main/src/openmdao/main/rbac.py
|
python
|
Credentials.encode
|
(self)
|
return (self.data, self.signature, self.client_creds)
|
Return object to be sent: ``(data, signature, client_creds)``.
|
Return object to be sent: ``(data, signature, client_creds)``.
|
[
"Return",
"object",
"to",
"be",
"sent",
":",
"(",
"data",
"signature",
"client_creds",
")",
"."
] |
def encode(self):
""" Return object to be sent: ``(data, signature, client_creds)``. """
return (self.data, self.signature, self.client_creds)
|
[
"def",
"encode",
"(",
"self",
")",
":",
"return",
"(",
"self",
".",
"data",
",",
"self",
".",
"signature",
",",
"self",
".",
"client_creds",
")"
] |
https://github.com/OpenMDAO/OpenMDAO-Framework/blob/f2e37b7de3edeaaeb2d251b375917adec059db9b/openmdao.main/src/openmdao/main/rbac.py#L155-L157
|
|
JasperSnoek/spearmint
|
b37a541be1ea035f82c7c82bbd93f5b4320e7d91
|
spearmint/spearmint/chooser/cma.py
|
python
|
Options.set
|
(self, dic, val=None, warn=True)
|
return self
|
set can assign versatile options from `Options.versatileOptions()`
with a new value, use `init()` for the others.
Arguments
---------
`dic`
either a dictionary or a key. In the latter
case, val must be provided
`val`
value for key
`warn`
bool, print a warning if the option cannot be changed
and is therefore omitted
This method will be most probably used with the ``opts`` attribute of
a `CMAEvolutionStrategy` instance.
|
set can assign versatile options from `Options.versatileOptions()`
with a new value, use `init()` for the others.
|
[
"set",
"can",
"assign",
"versatile",
"options",
"from",
"Options",
".",
"versatileOptions",
"()",
"with",
"a",
"new",
"value",
"use",
"init",
"()",
"for",
"the",
"others",
"."
] |
def set(self, dic, val=None, warn=True):
"""set can assign versatile options from `Options.versatileOptions()`
with a new value, use `init()` for the others.
Arguments
---------
`dic`
either a dictionary or a key. In the latter
case, val must be provided
`val`
value for key
`warn`
bool, print a warning if the option cannot be changed
and is therefore omitted
This method will be most probably used with the ``opts`` attribute of
a `CMAEvolutionStrategy` instance.
"""
if val is not None: # dic is a key in this case
dic = {dic:val} # compose a dictionary
for key, val in list(dic.items()):
if key in Options.versatileOptions():
self[key] = val
elif warn:
print('Warning in cma.Options.set(): key ' + str(key) + ' ignored')
return self
|
[
"def",
"set",
"(",
"self",
",",
"dic",
",",
"val",
"=",
"None",
",",
"warn",
"=",
"True",
")",
":",
"if",
"val",
"is",
"not",
"None",
":",
"# dic is a key in this case",
"dic",
"=",
"{",
"dic",
":",
"val",
"}",
"# compose a dictionary",
"for",
"key",
",",
"val",
"in",
"list",
"(",
"dic",
".",
"items",
"(",
")",
")",
":",
"if",
"key",
"in",
"Options",
".",
"versatileOptions",
"(",
")",
":",
"self",
"[",
"key",
"]",
"=",
"val",
"elif",
"warn",
":",
"print",
"(",
"'Warning in cma.Options.set(): key '",
"+",
"str",
"(",
"key",
")",
"+",
"' ignored'",
")",
"return",
"self"
] |
https://github.com/JasperSnoek/spearmint/blob/b37a541be1ea035f82c7c82bbd93f5b4320e7d91/spearmint/spearmint/chooser/cma.py#L2815-L2841
|
|
tensorflow/lingvo
|
ce10019243d954c3c3ebe739f7589b5eebfdf907
|
lingvo/core/py_utils.py
|
python
|
GetOrCreateGlobalStepVar
|
()
|
Return the global_step variable, creating it if it does not exist.
Prefer GetGlobalStep if a tensor rather than a tf.Variable is sufficient.
Returns:
The global_step variable, or a new created one if it does not exist.
|
Return the global_step variable, creating it if it does not exist.
|
[
"Return",
"the",
"global_step",
"variable",
"creating",
"it",
"if",
"it",
"does",
"not",
"exist",
"."
] |
def GetOrCreateGlobalStepVar():
"""Return the global_step variable, creating it if it does not exist.
Prefer GetGlobalStep if a tensor rather than a tf.Variable is sufficient.
Returns:
The global_step variable, or a new created one if it does not exist.
"""
with tf.variable_scope(GetGlobalVariableScope(), use_resource=True):
if _FromGlobal('pin_vars_to_cpu'):
with tf.device('/cpu:0'):
return tf.train.get_or_create_global_step()
else:
return tf.train.get_or_create_global_step()
|
[
"def",
"GetOrCreateGlobalStepVar",
"(",
")",
":",
"with",
"tf",
".",
"variable_scope",
"(",
"GetGlobalVariableScope",
"(",
")",
",",
"use_resource",
"=",
"True",
")",
":",
"if",
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"'pin_vars_to_cpu'",
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"'/cpu:0'",
")",
":",
"return",
"tf",
".",
"train",
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"get_or_create_global_step",
"(",
")",
"else",
":",
"return",
"tf",
".",
"train",
".",
"get_or_create_global_step",
"(",
")"
] |
https://github.com/tensorflow/lingvo/blob/ce10019243d954c3c3ebe739f7589b5eebfdf907/lingvo/core/py_utils.py#L2429-L2442
|
||
pandas-dev/pandas
|
5ba7d714014ae8feaccc0dd4a98890828cf2832d
|
pandas/io/pytables.py
|
python
|
IndexCol.is_indexed
|
(self)
|
return getattr(self.table.cols, self.cname).is_indexed
|
return whether I am an indexed column
|
return whether I am an indexed column
|
[
"return",
"whether",
"I",
"am",
"an",
"indexed",
"column"
] |
def is_indexed(self) -> bool:
"""return whether I am an indexed column"""
if not hasattr(self.table, "cols"):
# e.g. if infer hasn't been called yet, self.table will be None.
return False
return getattr(self.table.cols, self.cname).is_indexed
|
[
"def",
"is_indexed",
"(",
"self",
")",
"->",
"bool",
":",
"if",
"not",
"hasattr",
"(",
"self",
".",
"table",
",",
"\"cols\"",
")",
":",
"# e.g. if infer hasn't been called yet, self.table will be None.",
"return",
"False",
"return",
"getattr",
"(",
"self",
".",
"table",
".",
"cols",
",",
"self",
".",
"cname",
")",
".",
"is_indexed"
] |
https://github.com/pandas-dev/pandas/blob/5ba7d714014ae8feaccc0dd4a98890828cf2832d/pandas/io/pytables.py#L2050-L2055
|
|
ganglia/gmond_python_modules
|
2f7fcab3d27926ef4a2feb1b53c09af16a43e729
|
passenger/python_modules/passenger.py
|
python
|
UpdateMetricThread.update_metric
|
(self)
|
[] |
def update_metric(self):
status_output = timeout_command(self.status, self.timeout)
status_output += timeout_command(self.memory_stats, self.timeout)[-1:] # to get last line of memory output
dprint("%s", status_output)
for line in status_output:
for (name,regex) in self.status_regex.iteritems():
result = re.search(regex,line)
if result:
dprint("%s = %d", name, int(result.group(1)))
self.metric[self.mp+'_'+name] = int(result.group(1))
|
[
"def",
"update_metric",
"(",
"self",
")",
":",
"status_output",
"=",
"timeout_command",
"(",
"self",
".",
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",",
"self",
".",
"timeout",
")",
"status_output",
"+=",
"timeout_command",
"(",
"self",
".",
"memory_stats",
",",
"self",
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"timeout",
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"[",
"-",
"1",
":",
"]",
"# to get last line of memory output",
"dprint",
"(",
"\"%s\"",
",",
"status_output",
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"+",
"name",
"]",
"=",
"int",
"(",
"result",
".",
"group",
"(",
"1",
")",
")"
] |
https://github.com/ganglia/gmond_python_modules/blob/2f7fcab3d27926ef4a2feb1b53c09af16a43e729/passenger/python_modules/passenger.py#L76-L85
|
||||
crossbario/crossbar
|
ed350b7ba1c8421f3640b9c2e94a21ed4cfdff64
|
crossbar/router/service.py
|
python
|
RouterServiceAgent.subscription_get_events
|
(self, subscription_id, limit=10, details=None)
|
Return history of events for given subscription.
:param subscription_id: The ID of the subscription to get events for.
:type subscription_id: int
:param limit: Return at most this many events.
:type limit: int
:returns: List of events.
:rtype: list
|
Return history of events for given subscription.
|
[
"Return",
"history",
"of",
"events",
"for",
"given",
"subscription",
"."
] |
def subscription_get_events(self, subscription_id, limit=10, details=None):
"""
Return history of events for given subscription.
:param subscription_id: The ID of the subscription to get events for.
:type subscription_id: int
:param limit: Return at most this many events.
:type limit: int
:returns: List of events.
:rtype: list
"""
self.log.debug('subscription_get_events({subscription_id}, {limit})',
subscription_id=subscription_id,
limit=limit)
if not self._router._broker._event_store:
raise ApplicationError(
'wamp.error.history_unavailable',
message='event history not available or enabled',
)
subscription = self._router._broker._subscription_map.get_observation_by_id(subscription_id)
if subscription:
if is_protected_uri(subscription.uri, details):
raise ApplicationError(
ApplicationError.NOT_AUTHORIZED,
message='not authorized to retrieve event history for protected URI "{}"'.format(subscription.uri),
)
events = self._router._broker._event_store.get_events(subscription_id, limit)
if events is None:
# a return value of None in above signals that event history really
# is not available/enabled (which is different from an empty history!)
raise ApplicationError(
'wamp.error.history_unavailable',
message='event history for the given subscription is not available or enabled',
)
else:
return events
else:
raise ApplicationError(
ApplicationError.NO_SUCH_SUBSCRIPTION,
'no subscription with ID {} exists on this broker'.format(subscription_id),
)
|
[
"def",
"subscription_get_events",
"(",
"self",
",",
"subscription_id",
",",
"limit",
"=",
"10",
",",
"details",
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"None",
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":",
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"'subscription_get_events({subscription_id}, {limit})'",
",",
"subscription_id",
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",",
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"=",
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"if",
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"_router",
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"_broker",
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"'wamp.error.history_unavailable'",
",",
"message",
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",",
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"_router",
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"_event_store",
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"get_events",
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"subscription_id",
",",
"limit",
")",
"if",
"events",
"is",
"None",
":",
"# a return value of None in above signals that event history really",
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"raise",
"ApplicationError",
"(",
"'wamp.error.history_unavailable'",
",",
"message",
"=",
"'event history for the given subscription is not available or enabled'",
",",
")",
"else",
":",
"return",
"events",
"else",
":",
"raise",
"ApplicationError",
"(",
"ApplicationError",
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"NO_SUCH_SUBSCRIPTION",
",",
"'no subscription with ID {} exists on this broker'",
".",
"format",
"(",
"subscription_id",
")",
",",
")"
] |
https://github.com/crossbario/crossbar/blob/ed350b7ba1c8421f3640b9c2e94a21ed4cfdff64/crossbar/router/service.py#L903-L948
|
||
fedora-infra/anitya
|
cc01878ac023790646a76eb4cbef45d639e2372c
|
anitya/db/migrations/versions/2d1aa7ff82a5_remove_code_google_backend.py
|
python
|
upgrade
|
()
|
Change backend of projects with code google backend to custom.
|
Change backend of projects with code google backend to custom.
|
[
"Change",
"backend",
"of",
"projects",
"with",
"code",
"google",
"backend",
"to",
"custom",
"."
] |
def upgrade():
"""
Change backend of projects with code google backend to custom.
"""
op.execute(
"""
UPDATE projects
SET backend='custom'
WHERE backend='Google code'
"""
)
|
[
"def",
"upgrade",
"(",
")",
":",
"op",
".",
"execute",
"(",
"\"\"\"\n UPDATE projects\n SET backend='custom'\n WHERE backend='Google code'\n \"\"\"",
")"
] |
https://github.com/fedora-infra/anitya/blob/cc01878ac023790646a76eb4cbef45d639e2372c/anitya/db/migrations/versions/2d1aa7ff82a5_remove_code_google_backend.py#L16-L26
|
||
sleventyeleven/linuxprivchecker
|
0d701080bbf92efd464e97d71a70f97c6f2cd658
|
linuxprivchecker.py
|
python
|
enum_user_info
|
()
|
return userinfo
|
Enumerate User Information (enum_user_info)
Enumerate current user information and save the results
:return: Dictionary with the user information commands and results
|
Enumerate User Information (enum_user_info)
Enumerate current user information and save the results
|
[
"Enumerate",
"User",
"Information",
"(",
"enum_user_info",
")",
"Enumerate",
"current",
"user",
"information",
"and",
"save",
"the",
"results"
] |
def enum_user_info():
"""
Enumerate User Information (enum_user_info)
Enumerate current user information and save the results
:return: Dictionary with the user information commands and results
"""
print "\n[*] ENUMERATING USER AND ENVIRONMENTAL INFO...\n"
userinfo = {
"WHOAMI": {"cmd": "whoami", "msg": "Current User", "results": []},
"ID": {"cmd": "id", "msg": "Current User ID", "results": []},
"ALLUSERS": {"cmd": "cat /etc/passwd", "msg": "All users", "results": []},
"SUPUSERS": {"cmd": "grep -v -E '^#' /etc/passwd | awk -F: '$3 == 0{print $1}'", "msg": "Super Users Found:", "results": []},
"ENV": {"cmd": "env 2>/dev/null | grep -v 'LS_COLORS'", "msg": "Environment", "results": []},
"SUDOERS": {"cmd": "cat /etc/sudoers 2>/dev/null | grep -v '#' 2>/dev/null", "msg": "Sudoers (privileged)", "results": []},
"SCREENS": {"cmd": "screen -ls 2>/dev/null", "msg": "List out any screens running for the current user", "results": []},
"LOGGEDIN": {"cmd": "who -a 2>/dev/null", "msg": "Logged in User Activity", "results": []}
}
userinfo = execute_cmd(userinfo)
print_results(userinfo)
if "root" in userinfo["ID"]["results"][0]:
print "[!] ARE YOU SURE YOU'RE NOT ROOT ALREADY?\n"
exit()
return userinfo
|
[
"def",
"enum_user_info",
"(",
")",
":",
"print",
"\"\\n[*] ENUMERATING USER AND ENVIRONMENTAL INFO...\\n\"",
"userinfo",
"=",
"{",
"\"WHOAMI\"",
":",
"{",
"\"cmd\"",
":",
"\"whoami\"",
",",
"\"msg\"",
":",
"\"Current User\"",
",",
"\"results\"",
":",
"[",
"]",
"}",
",",
"\"ID\"",
":",
"{",
"\"cmd\"",
":",
"\"id\"",
",",
"\"msg\"",
":",
"\"Current User ID\"",
",",
"\"results\"",
":",
"[",
"]",
"}",
",",
"\"ALLUSERS\"",
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"{",
"\"cmd\"",
":",
"\"cat /etc/passwd\"",
",",
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"\"All users\"",
",",
"\"results\"",
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"[",
"]",
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",",
"\"SUPUSERS\"",
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"\"cmd\"",
":",
"\"grep -v -E '^#' /etc/passwd | awk -F: '$3 == 0{print $1}'\"",
",",
"\"msg\"",
":",
"\"Super Users Found:\"",
",",
"\"results\"",
":",
"[",
"]",
"}",
",",
"\"ENV\"",
":",
"{",
"\"cmd\"",
":",
"\"env 2>/dev/null | grep -v 'LS_COLORS'\"",
",",
"\"msg\"",
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"\"Environment\"",
",",
"\"results\"",
":",
"[",
"]",
"}",
",",
"\"SUDOERS\"",
":",
"{",
"\"cmd\"",
":",
"\"cat /etc/sudoers 2>/dev/null | grep -v '#' 2>/dev/null\"",
",",
"\"msg\"",
":",
"\"Sudoers (privileged)\"",
",",
"\"results\"",
":",
"[",
"]",
"}",
",",
"\"SCREENS\"",
":",
"{",
"\"cmd\"",
":",
"\"screen -ls 2>/dev/null\"",
",",
"\"msg\"",
":",
"\"List out any screens running for the current user\"",
",",
"\"results\"",
":",
"[",
"]",
"}",
",",
"\"LOGGEDIN\"",
":",
"{",
"\"cmd\"",
":",
"\"who -a 2>/dev/null\"",
",",
"\"msg\"",
":",
"\"Logged in User Activity\"",
",",
"\"results\"",
":",
"[",
"]",
"}",
"}",
"userinfo",
"=",
"execute_cmd",
"(",
"userinfo",
")",
"print_results",
"(",
"userinfo",
")",
"if",
"\"root\"",
"in",
"userinfo",
"[",
"\"ID\"",
"]",
"[",
"\"results\"",
"]",
"[",
"0",
"]",
":",
"print",
"\"[!] ARE YOU SURE YOU'RE NOT ROOT ALREADY?\\n\"",
"exit",
"(",
")",
"return",
"userinfo"
] |
https://github.com/sleventyeleven/linuxprivchecker/blob/0d701080bbf92efd464e97d71a70f97c6f2cd658/linuxprivchecker.py#L164-L191
|
|
openstack/designate
|
bff3d5f6e31fe595a77143ec4ac779c187bf72a8
|
designate/api/v2/controllers/zones/__init__.py
|
python
|
ZonesController.get_one
|
(self, zone_id)
|
return DesignateAdapter.render(
'API_v2',
zone,
request=request)
|
Get Zone
|
Get Zone
|
[
"Get",
"Zone"
] |
def get_one(self, zone_id):
"""Get Zone"""
# TODO(kiall): Validate we have a sane UUID for zone_id
request = pecan.request
context = request.environ['context']
zone = self.central_api.get_zone(context, zone_id)
LOG.info("Retrieved %(zone)s", {'zone': zone})
return DesignateAdapter.render(
'API_v2',
zone,
request=request)
|
[
"def",
"get_one",
"(",
"self",
",",
"zone_id",
")",
":",
"# TODO(kiall): Validate we have a sane UUID for zone_id",
"request",
"=",
"pecan",
".",
"request",
"context",
"=",
"request",
".",
"environ",
"[",
"'context'",
"]",
"zone",
"=",
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"central_api",
".",
"get_zone",
"(",
"context",
",",
"zone_id",
")",
"LOG",
".",
"info",
"(",
"\"Retrieved %(zone)s\"",
",",
"{",
"'zone'",
":",
"zone",
"}",
")",
"return",
"DesignateAdapter",
".",
"render",
"(",
"'API_v2'",
",",
"zone",
",",
"request",
"=",
"request",
")"
] |
https://github.com/openstack/designate/blob/bff3d5f6e31fe595a77143ec4ac779c187bf72a8/designate/api/v2/controllers/zones/__init__.py#L46-L60
|
|
holzschu/Carnets
|
44effb10ddfc6aa5c8b0687582a724ba82c6b547
|
Library/lib/python3.7/site-packages/matplotlib-3.0.3-py3.7-macosx-10.9-x86_64.egg/matplotlib/afm.py
|
python
|
AFM.get_width_from_char_name
|
(self, name)
|
return self._metrics_by_name[name].width
|
Get the width of the character from a type1 character name.
|
Get the width of the character from a type1 character name.
|
[
"Get",
"the",
"width",
"of",
"the",
"character",
"from",
"a",
"type1",
"character",
"name",
"."
] |
def get_width_from_char_name(self, name):
"""Get the width of the character from a type1 character name."""
return self._metrics_by_name[name].width
|
[
"def",
"get_width_from_char_name",
"(",
"self",
",",
"name",
")",
":",
"return",
"self",
".",
"_metrics_by_name",
"[",
"name",
"]",
".",
"width"
] |
https://github.com/holzschu/Carnets/blob/44effb10ddfc6aa5c8b0687582a724ba82c6b547/Library/lib/python3.7/site-packages/matplotlib-3.0.3-py3.7-macosx-10.9-x86_64.egg/matplotlib/afm.py#L478-L480
|
|
dpressel/mead-baseline
|
9987e6b37fa6525a4ddc187c305e292a718f59a9
|
layers/eight_mile/bleu.py
|
python
|
geometric_mean
|
(precision: np.ndarray)
|
return np.exp(np.mean(np.log(precision))).item()
|
Calculate the geometric mean of the precision.
Geometric mean is the nth root of the product of n numbers. This
can be expressed as the e^(arithmetic mean of the logs). The geometric
mean only applies to positive number and any 0 is the values makes the
answer trivially zero to checkout for that first to avoid log(0).
:param precision: The precision for each n-gram size.
:returns: The geometric_mean of the values.
|
Calculate the geometric mean of the precision.
|
[
"Calculate",
"the",
"geometric",
"mean",
"of",
"the",
"precision",
"."
] |
def geometric_mean(precision: np.ndarray) -> float:
"""Calculate the geometric mean of the precision.
Geometric mean is the nth root of the product of n numbers. This
can be expressed as the e^(arithmetic mean of the logs). The geometric
mean only applies to positive number and any 0 is the values makes the
answer trivially zero to checkout for that first to avoid log(0).
:param precision: The precision for each n-gram size.
:returns: The geometric_mean of the values.
"""
if np.min(precision) <= 0:
return 0.0
return np.exp(np.mean(np.log(precision))).item()
|
[
"def",
"geometric_mean",
"(",
"precision",
":",
"np",
".",
"ndarray",
")",
"->",
"float",
":",
"if",
"np",
".",
"min",
"(",
"precision",
")",
"<=",
"0",
":",
"return",
"0.0",
"return",
"np",
".",
"exp",
"(",
"np",
".",
"mean",
"(",
"np",
".",
"log",
"(",
"precision",
")",
")",
")",
".",
"item",
"(",
")"
] |
https://github.com/dpressel/mead-baseline/blob/9987e6b37fa6525a4ddc187c305e292a718f59a9/layers/eight_mile/bleu.py#L205-L219
|
|
spesmilo/electrum
|
bdbd59300fbd35b01605e66145458e5f396108e8
|
electrum/plugins/safe_t/safe_t.py
|
python
|
SafeTPlugin.get_safet_input_script_type
|
(self, electrum_txin_type: str)
|
[] |
def get_safet_input_script_type(self, electrum_txin_type: str):
if electrum_txin_type in ('p2wpkh', 'p2wsh'):
return self.types.InputScriptType.SPENDWITNESS
if electrum_txin_type in ('p2wpkh-p2sh', 'p2wsh-p2sh'):
return self.types.InputScriptType.SPENDP2SHWITNESS
if electrum_txin_type in ('p2pkh',):
return self.types.InputScriptType.SPENDADDRESS
if electrum_txin_type in ('p2sh',):
return self.types.InputScriptType.SPENDMULTISIG
raise ValueError('unexpected txin type: {}'.format(electrum_txin_type))
|
[
"def",
"get_safet_input_script_type",
"(",
"self",
",",
"electrum_txin_type",
":",
"str",
")",
":",
"if",
"electrum_txin_type",
"in",
"(",
"'p2wpkh'",
",",
"'p2wsh'",
")",
":",
"return",
"self",
".",
"types",
".",
"InputScriptType",
".",
"SPENDWITNESS",
"if",
"electrum_txin_type",
"in",
"(",
"'p2wpkh-p2sh'",
",",
"'p2wsh-p2sh'",
")",
":",
"return",
"self",
".",
"types",
".",
"InputScriptType",
".",
"SPENDP2SHWITNESS",
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"electrum_txin_type",
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")",
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"types",
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"InputScriptType",
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"SPENDADDRESS",
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"electrum_txin_type",
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"'p2sh'",
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":",
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"self",
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"types",
".",
"InputScriptType",
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"SPENDMULTISIG",
"raise",
"ValueError",
"(",
"'unexpected txin type: {}'",
".",
"format",
"(",
"electrum_txin_type",
")",
")"
] |
https://github.com/spesmilo/electrum/blob/bdbd59300fbd35b01605e66145458e5f396108e8/electrum/plugins/safe_t/safe_t.py#L276-L285
|
||||
googleads/google-ads-python
|
2a1d6062221f6aad1992a6bcca0e7e4a93d2db86
|
google/ads/googleads/v8/services/services/dynamic_search_ads_search_term_view_service/client.py
|
python
|
DynamicSearchAdsSearchTermViewServiceClient.common_folder_path
|
(folder: str,)
|
return "folders/{folder}".format(folder=folder,)
|
Return a fully-qualified folder string.
|
Return a fully-qualified folder string.
|
[
"Return",
"a",
"fully",
"-",
"qualified",
"folder",
"string",
"."
] |
def common_folder_path(folder: str,) -> str:
"""Return a fully-qualified folder string."""
return "folders/{folder}".format(folder=folder,)
|
[
"def",
"common_folder_path",
"(",
"folder",
":",
"str",
",",
")",
"->",
"str",
":",
"return",
"\"folders/{folder}\"",
".",
"format",
"(",
"folder",
"=",
"folder",
",",
")"
] |
https://github.com/googleads/google-ads-python/blob/2a1d6062221f6aad1992a6bcca0e7e4a93d2db86/google/ads/googleads/v8/services/services/dynamic_search_ads_search_term_view_service/client.py#L213-L215
|
|
jina-ai/jina
|
c77a492fcd5adba0fc3de5347bea83dd4e7d8087
|
jina/hubble/hubapi.py
|
python
|
get_lockfile
|
()
|
return str(_hub_root / 'LOCK')
|
Get the path of file locker
:return: the path of file locker
|
Get the path of file locker
:return: the path of file locker
|
[
"Get",
"the",
"path",
"of",
"file",
"locker",
":",
"return",
":",
"the",
"path",
"of",
"file",
"locker"
] |
def get_lockfile() -> str:
"""Get the path of file locker
:return: the path of file locker
"""
return str(_hub_root / 'LOCK')
|
[
"def",
"get_lockfile",
"(",
")",
"->",
"str",
":",
"return",
"str",
"(",
"_hub_root",
"/",
"'LOCK'",
")"
] |
https://github.com/jina-ai/jina/blob/c77a492fcd5adba0fc3de5347bea83dd4e7d8087/jina/hubble/hubapi.py#L55-L59
|
|
home-assistant/core
|
265ebd17a3f17ed8dc1e9bdede03ac8e323f1ab1
|
homeassistant/components/blinksticklight/light.py
|
python
|
setup_platform
|
(
hass: HomeAssistant,
config: ConfigType,
add_entities: AddEntitiesCallback,
discovery_info: DiscoveryInfoType | None = None,
)
|
Set up Blinkstick device specified by serial number.
|
Set up Blinkstick device specified by serial number.
|
[
"Set",
"up",
"Blinkstick",
"device",
"specified",
"by",
"serial",
"number",
"."
] |
def setup_platform(
hass: HomeAssistant,
config: ConfigType,
add_entities: AddEntitiesCallback,
discovery_info: DiscoveryInfoType | None = None,
) -> None:
"""Set up Blinkstick device specified by serial number."""
name = config[CONF_NAME]
serial = config[CONF_SERIAL]
stick = blinkstick.find_by_serial(serial)
add_entities([BlinkStickLight(stick, name)], True)
|
[
"def",
"setup_platform",
"(",
"hass",
":",
"HomeAssistant",
",",
"config",
":",
"ConfigType",
",",
"add_entities",
":",
"AddEntitiesCallback",
",",
"discovery_info",
":",
"DiscoveryInfoType",
"|",
"None",
"=",
"None",
",",
")",
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"CONF_NAME",
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"CONF_SERIAL",
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"stick",
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"find_by_serial",
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"serial",
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"add_entities",
"(",
"[",
"BlinkStickLight",
"(",
"stick",
",",
"name",
")",
"]",
",",
"True",
")"
] |
https://github.com/home-assistant/core/blob/265ebd17a3f17ed8dc1e9bdede03ac8e323f1ab1/homeassistant/components/blinksticklight/light.py#L36-L49
|
||
P1sec/pycrate
|
d12bbccf1df8c9c7891a26967a9d2635610ec5b8
|
pycrate_core/elt.py
|
python
|
Element.to_int
|
(self)
|
Produce a signed integer from the internal value
Args:
None
Returns:
integ (int) : signed integer
|
Produce a signed integer from the internal value
Args:
None
Returns:
integ (int) : signed integer
|
[
"Produce",
"a",
"signed",
"integer",
"from",
"the",
"internal",
"value",
"Args",
":",
"None",
"Returns",
":",
"integ",
"(",
"int",
")",
":",
"signed",
"integer"
] |
def to_int(self):
"""Produce a signed integer from the internal value
Args:
None
Returns:
integ (int) : signed integer
"""
try:
return bytes_to_int(self.to_bytes(), self.get_bl())
except PycrateErr:
# an invalid value has been set, _SAFE_STAT / DYN is probably disabled
# for e.g. fuzzing purpose, but there is still need to not break here
b = self.to_bytes()
return bytes_to_int(b, len(b)<<3)
|
[
"def",
"to_int",
"(",
"self",
")",
":",
"try",
":",
"return",
"bytes_to_int",
"(",
"self",
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"to_bytes",
"(",
")",
",",
"self",
".",
"get_bl",
"(",
")",
")",
"except",
"PycrateErr",
":",
"# an invalid value has been set, _SAFE_STAT / DYN is probably disabled",
"# for e.g. fuzzing purpose, but there is still need to not break here",
"b",
"=",
"self",
".",
"to_bytes",
"(",
")",
"return",
"bytes_to_int",
"(",
"b",
",",
"len",
"(",
"b",
")",
"<<",
"3",
")"
] |
https://github.com/P1sec/pycrate/blob/d12bbccf1df8c9c7891a26967a9d2635610ec5b8/pycrate_core/elt.py#L720-L735
|
||
ansible/ansible-modules-extras
|
f216ba8e0616bc8ad8794c22d4b48e1ab18886cf
|
cloud/misc/virt.py
|
python
|
Virt.start
|
(self, vmid)
|
return self.conn.create(vmid)
|
Start the machine via the given id/name
|
Start the machine via the given id/name
|
[
"Start",
"the",
"machine",
"via",
"the",
"given",
"id",
"/",
"name"
] |
def start(self, vmid):
""" Start the machine via the given id/name """
self.__get_conn()
return self.conn.create(vmid)
|
[
"def",
"start",
"(",
"self",
",",
"vmid",
")",
":",
"self",
".",
"__get_conn",
"(",
")",
"return",
"self",
".",
"conn",
".",
"create",
"(",
"vmid",
")"
] |
https://github.com/ansible/ansible-modules-extras/blob/f216ba8e0616bc8ad8794c22d4b48e1ab18886cf/cloud/misc/virt.py#L374-L378
|
|
h2oai/h2o4gpu
|
aaf7795d3c3be430129eacfd99d598da0cc838e7
|
src/interface_py/h2o4gpu/types.py
|
python
|
make_settings
|
(double_precision=False, **kwargs)
|
return settings
|
Creates a SettingsS objects from key-values
:param double_precision: boolean, optional, default : False
:param kwargs: **kwargs
:return: SettingsS object
|
Creates a SettingsS objects from key-values
|
[
"Creates",
"a",
"SettingsS",
"objects",
"from",
"key",
"-",
"values"
] |
def make_settings(double_precision=False, **kwargs):
"""Creates a SettingsS objects from key-values
:param double_precision: boolean, optional, default : False
:param kwargs: **kwargs
:return: SettingsS object
"""
settings = lazyLib().H2O4GPUSettingsD if double_precision \
else lazyLib().H2O4GPUSettingsS
settings.rho = kwargs['rho'] if 'rho' in list(
kwargs.keys()) else H2OSolverDefault.RHO
settings.relt = kwargs['abs_tol'] if 'abs_tol' in list(
kwargs.keys()) else H2OSolverDefault.ABS_TOL
settings.abst = kwargs['rel_tol'] if 'rel_tol' in list(
kwargs.keys()) else H2OSolverDefault.REL_TOL
settings.maxit = kwargs['max_iters'] if 'max_iters' in list(
kwargs.keys()) else H2OSolverDefault.MAX_ITERS
settings.verb = kwargs['verbose'] if 'verbose' in list(
kwargs.keys()) else H2OSolverDefault.VERBOSE
settings.adap = kwargs['adaptive_rho'] if 'adaptive_rho' in list(
kwargs.keys()) else H2OSolverDefault.ADAPTIVE_RHO
settings.equil = kwargs['equil'] if 'equil' in list(
kwargs.keys()) else H2OSolverDefault.EQUIL
settings.gaps = kwargs['gap_stop'] if 'gap_stop' in list(
kwargs.keys()) else H2OSolverDefault.GAP_STOP
settings.warm = kwargs['warm_start'] if 'warm_start' in list(
kwargs.keys()) else H2OSolverDefault.WARM_START
settings.ndev = kwargs['nDev'] if 'nDev' in list(
kwargs.keys()) else H2OSolverDefault.N_DEV
settings.wdev = kwargs['wDev'] if 'wDev' in list(
kwargs.keys()) else H2OSolverDefault.W_DEV
return settings
|
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",",
"*",
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"kwargs",
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"'gap_stop'",
"]",
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"(",
"kwargs",
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"keys",
"(",
")",
")",
"else",
"H2OSolverDefault",
".",
"GAP_STOP",
"settings",
".",
"warm",
"=",
"kwargs",
"[",
"'warm_start'",
"]",
"if",
"'warm_start'",
"in",
"list",
"(",
"kwargs",
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"keys",
"(",
")",
")",
"else",
"H2OSolverDefault",
".",
"WARM_START",
"settings",
".",
"ndev",
"=",
"kwargs",
"[",
"'nDev'",
"]",
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"'nDev'",
"in",
"list",
"(",
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"keys",
"(",
")",
")",
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"H2OSolverDefault",
".",
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".",
"wdev",
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"kwargs",
"[",
"'wDev'",
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"'wDev'",
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"(",
"kwargs",
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"keys",
"(",
")",
")",
"else",
"H2OSolverDefault",
".",
"W_DEV",
"return",
"settings"
] |
https://github.com/h2oai/h2o4gpu/blob/aaf7795d3c3be430129eacfd99d598da0cc838e7/src/interface_py/h2o4gpu/types.py#L90-L121
|
|
Anaconda-Platform/anaconda-project
|
df5ec33c12591e6512436d38d36c6132fa2e9618
|
anaconda_project/internal/cli/environment_commands.py
|
python
|
main_remove_packages
|
(args)
|
return remove_packages(args.directory, args.env_spec, args.packages, args.pip)
|
Start the remove-packages command and return exit status code.
|
Start the remove-packages command and return exit status code.
|
[
"Start",
"the",
"remove",
"-",
"packages",
"command",
"and",
"return",
"exit",
"status",
"code",
"."
] |
def main_remove_packages(args):
"""Start the remove-packages command and return exit status code."""
return remove_packages(args.directory, args.env_spec, args.packages, args.pip)
|
[
"def",
"main_remove_packages",
"(",
"args",
")",
":",
"return",
"remove_packages",
"(",
"args",
".",
"directory",
",",
"args",
".",
"env_spec",
",",
"args",
".",
"packages",
",",
"args",
".",
"pip",
")"
] |
https://github.com/Anaconda-Platform/anaconda-project/blob/df5ec33c12591e6512436d38d36c6132fa2e9618/anaconda_project/internal/cli/environment_commands.py#L196-L198
|
|
BMW-InnovationLab/BMW-TensorFlow-Training-GUI
|
4f10d1f00f9ac312ca833e5b28fd0f8952cfee17
|
training_api/research/object_detection/metrics/coco_tools.py
|
python
|
ExportSingleImageDetectionMasksToCoco
|
(image_id,
category_id_set,
detection_masks,
detection_scores,
detection_classes)
|
return detections_list
|
Export detection masks of a single image to COCO format.
This function converts detections represented as numpy arrays to dictionaries
that can be ingested by the COCO evaluation API. We assume that
detection_masks, detection_scores, and detection_classes are in correspondence
- that is: detection_masks[i, :], detection_classes[i] and detection_scores[i]
are associated with the same annotation.
Args:
image_id: unique image identifier either of type integer or string.
category_id_set: A set of valid class ids. Detections with classes not in
category_id_set are dropped.
detection_masks: uint8 numpy array of shape [num_detections, image_height,
image_width] containing detection_masks.
detection_scores: float numpy array of shape [num_detections] containing
scores for detection masks.
detection_classes: integer numpy array of shape [num_detections] containing
the classes for detection masks.
Returns:
a list of detection mask annotations for a single image in the COCO format.
Raises:
ValueError: if (1) detection_masks, detection_scores and detection_classes
do not have the right lengths or (2) if each of the elements inside these
lists do not have the correct shapes or (3) if image_ids are not integers.
|
Export detection masks of a single image to COCO format.
|
[
"Export",
"detection",
"masks",
"of",
"a",
"single",
"image",
"to",
"COCO",
"format",
"."
] |
def ExportSingleImageDetectionMasksToCoco(image_id,
category_id_set,
detection_masks,
detection_scores,
detection_classes):
"""Export detection masks of a single image to COCO format.
This function converts detections represented as numpy arrays to dictionaries
that can be ingested by the COCO evaluation API. We assume that
detection_masks, detection_scores, and detection_classes are in correspondence
- that is: detection_masks[i, :], detection_classes[i] and detection_scores[i]
are associated with the same annotation.
Args:
image_id: unique image identifier either of type integer or string.
category_id_set: A set of valid class ids. Detections with classes not in
category_id_set are dropped.
detection_masks: uint8 numpy array of shape [num_detections, image_height,
image_width] containing detection_masks.
detection_scores: float numpy array of shape [num_detections] containing
scores for detection masks.
detection_classes: integer numpy array of shape [num_detections] containing
the classes for detection masks.
Returns:
a list of detection mask annotations for a single image in the COCO format.
Raises:
ValueError: if (1) detection_masks, detection_scores and detection_classes
do not have the right lengths or (2) if each of the elements inside these
lists do not have the correct shapes or (3) if image_ids are not integers.
"""
if len(detection_classes.shape) != 1 or len(detection_scores.shape) != 1:
raise ValueError('All entries in detection_classes and detection_scores'
'expected to be of rank 1.')
num_boxes = detection_classes.shape[0]
if not num_boxes == len(detection_masks) == detection_scores.shape[0]:
raise ValueError('Corresponding entries in detection_classes, '
'detection_scores and detection_masks should have '
'compatible lengths and shapes '
'Classes length: %d. Masks length: %d. '
'Scores length: %d' % (
detection_classes.shape[0], len(detection_masks),
detection_scores.shape[0]
))
detections_list = []
for i in range(num_boxes):
if detection_classes[i] in category_id_set:
detections_list.append({
'image_id': image_id,
'category_id': int(detection_classes[i]),
'segmentation': _RleCompress(detection_masks[i]),
'score': float(detection_scores[i])
})
return detections_list
|
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")",
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] |
https://github.com/BMW-InnovationLab/BMW-TensorFlow-Training-GUI/blob/4f10d1f00f9ac312ca833e5b28fd0f8952cfee17/training_api/research/object_detection/metrics/coco_tools.py#L552-L607
|
|
openshift/openshift-tools
|
1188778e728a6e4781acf728123e5b356380fe6f
|
openshift/installer/vendored/openshift-ansible-3.9.14-1/roles/lib_openshift/library/oc_obj.py
|
python
|
OCObject.get
|
(self)
|
return results
|
return a kind by name
|
return a kind by name
|
[
"return",
"a",
"kind",
"by",
"name"
] |
def get(self):
'''return a kind by name '''
results = self._get(self.kind, name=self.name, selector=self.selector, field_selector=self.field_selector)
if (results['returncode'] != 0 and 'stderr' in results and
'\"{}\" not found'.format(self.name) in results['stderr']):
results['returncode'] = 0
return results
|
[
"def",
"get",
"(",
"self",
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":",
"results",
"=",
"self",
".",
"_get",
"(",
"self",
".",
"kind",
",",
"name",
"=",
"self",
".",
"name",
",",
"selector",
"=",
"self",
".",
"selector",
",",
"field_selector",
"=",
"self",
".",
"field_selector",
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"if",
"(",
"results",
"[",
"'returncode'",
"]",
"!=",
"0",
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"'stderr'",
"in",
"results",
"and",
"'\\\"{}\\\" not found'",
".",
"format",
"(",
"self",
".",
"name",
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"in",
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"[",
"'stderr'",
"]",
")",
":",
"results",
"[",
"'returncode'",
"]",
"=",
"0",
"return",
"results"
] |
https://github.com/openshift/openshift-tools/blob/1188778e728a6e4781acf728123e5b356380fe6f/openshift/installer/vendored/openshift-ansible-3.9.14-1/roles/lib_openshift/library/oc_obj.py#L1513-L1520
|
|
Dentosal/python-sc2
|
e816cce83772d1aee1291b86b300b69405aa96b4
|
sc2/unit.py
|
python
|
PassengerUnit.armor
|
(self)
|
return self._type_data._proto.armor
|
Does not include upgrades
|
Does not include upgrades
|
[
"Does",
"not",
"include",
"upgrades"
] |
def armor(self) -> Union[int, float]:
""" Does not include upgrades """
return self._type_data._proto.armor
|
[
"def",
"armor",
"(",
"self",
")",
"->",
"Union",
"[",
"int",
",",
"float",
"]",
":",
"return",
"self",
".",
"_type_data",
".",
"_proto",
".",
"armor"
] |
https://github.com/Dentosal/python-sc2/blob/e816cce83772d1aee1291b86b300b69405aa96b4/sc2/unit.py#L180-L182
|
|
GaoPeng97/transformer-xl-chinese
|
ecb924f2e6e97955054ef134edc11f72279d18bb
|
tf/data_utils.py
|
python
|
get_bin_sizes
|
(data, batch_size, tgt_len, cutoffs, std_mult=[2.5, 2.5, 2.5])
|
return bin_sizes
|
Note: the `batch_size` here should be per-core batch size
|
Note: the `batch_size` here should be per-core batch size
|
[
"Note",
":",
"the",
"batch_size",
"here",
"should",
"be",
"per",
"-",
"core",
"batch",
"size"
] |
def get_bin_sizes(data, batch_size, tgt_len, cutoffs, std_mult=[2.5, 2.5, 2.5]):
"""
Note: the `batch_size` here should be per-core batch size
"""
bin_sizes = []
def _nearest_to_eight(x): # so that it's faster on TPUs
y = x - x % 8
return y + 8 if x % 8 >= 4 else max(8, y)
if cutoffs:
print('======={}======================={}=============================='.format(batch_size, tgt_len))
num_batch = len(data) // batch_size // tgt_len
data = data[:batch_size * num_batch * tgt_len]
data = data.reshape(batch_size, num_batch, tgt_len)
tot = batch_size * tgt_len
for b, (left, right) in enumerate(zip(cutoffs[1:-1], cutoffs[2:])):
mask = (data >= left) * (data < right)
percents = mask.astype(np.float64).sum(2).sum(0) / tot
mean = np.mean(percents)
std = np.std(percents)
bin_size = int(math.ceil(tgt_len * batch_size * (mean + std_mult[b] * std)))
bin_size = _nearest_to_eight(bin_size)
bin_sizes.append(bin_size)
return bin_sizes
|
[
"def",
"get_bin_sizes",
"(",
"data",
",",
"batch_size",
",",
"tgt_len",
",",
"cutoffs",
",",
"std_mult",
"=",
"[",
"2.5",
",",
"2.5",
",",
"2.5",
"]",
")",
":",
"bin_sizes",
"=",
"[",
"]",
"def",
"_nearest_to_eight",
"(",
"x",
")",
":",
"# so that it's faster on TPUs",
"y",
"=",
"x",
"-",
"x",
"%",
"8",
"return",
"y",
"+",
"8",
"if",
"x",
"%",
"8",
">=",
"4",
"else",
"max",
"(",
"8",
",",
"y",
")",
"if",
"cutoffs",
":",
"print",
"(",
"'======={}======================={}=============================='",
".",
"format",
"(",
"batch_size",
",",
"tgt_len",
")",
")",
"num_batch",
"=",
"len",
"(",
"data",
")",
"//",
"batch_size",
"//",
"tgt_len",
"data",
"=",
"data",
"[",
":",
"batch_size",
"*",
"num_batch",
"*",
"tgt_len",
"]",
"data",
"=",
"data",
".",
"reshape",
"(",
"batch_size",
",",
"num_batch",
",",
"tgt_len",
")",
"tot",
"=",
"batch_size",
"*",
"tgt_len",
"for",
"b",
",",
"(",
"left",
",",
"right",
")",
"in",
"enumerate",
"(",
"zip",
"(",
"cutoffs",
"[",
"1",
":",
"-",
"1",
"]",
",",
"cutoffs",
"[",
"2",
":",
"]",
")",
")",
":",
"mask",
"=",
"(",
"data",
">=",
"left",
")",
"*",
"(",
"data",
"<",
"right",
")",
"percents",
"=",
"mask",
".",
"astype",
"(",
"np",
".",
"float64",
")",
".",
"sum",
"(",
"2",
")",
".",
"sum",
"(",
"0",
")",
"/",
"tot",
"mean",
"=",
"np",
".",
"mean",
"(",
"percents",
")",
"std",
"=",
"np",
".",
"std",
"(",
"percents",
")",
"bin_size",
"=",
"int",
"(",
"math",
".",
"ceil",
"(",
"tgt_len",
"*",
"batch_size",
"*",
"(",
"mean",
"+",
"std_mult",
"[",
"b",
"]",
"*",
"std",
")",
")",
")",
"bin_size",
"=",
"_nearest_to_eight",
"(",
"bin_size",
")",
"bin_sizes",
".",
"append",
"(",
"bin_size",
")",
"return",
"bin_sizes"
] |
https://github.com/GaoPeng97/transformer-xl-chinese/blob/ecb924f2e6e97955054ef134edc11f72279d18bb/tf/data_utils.py#L181-L209
|
|
sagemath/sage
|
f9b2db94f675ff16963ccdefba4f1a3393b3fe0d
|
src/sage/combinat/partition.py
|
python
|
RegularPartitions_n.cardinality
|
(self)
|
return ZZ.sum(1 for x in self)
|
Return the cardinality of ``self``.
EXAMPLES::
sage: P = Partitions(5, regular=3)
sage: P.cardinality()
5
sage: P = Partitions(5, regular=6)
sage: P.cardinality()
7
sage: P.cardinality() == Partitions(5).cardinality()
True
TESTS:
Check the corner case::
sage: P = Partitions(0, regular=3)
sage: P.cardinality()
1
Check for 1-regular partitions::
sage: P = Partitions(0, regular=1)
sage: P.cardinality()
1
sage: P = Partitions(5, regular=1)
sage: P.cardinality()
0
|
Return the cardinality of ``self``.
|
[
"Return",
"the",
"cardinality",
"of",
"self",
"."
] |
def cardinality(self):
"""
Return the cardinality of ``self``.
EXAMPLES::
sage: P = Partitions(5, regular=3)
sage: P.cardinality()
5
sage: P = Partitions(5, regular=6)
sage: P.cardinality()
7
sage: P.cardinality() == Partitions(5).cardinality()
True
TESTS:
Check the corner case::
sage: P = Partitions(0, regular=3)
sage: P.cardinality()
1
Check for 1-regular partitions::
sage: P = Partitions(0, regular=1)
sage: P.cardinality()
1
sage: P = Partitions(5, regular=1)
sage: P.cardinality()
0
"""
if self._ell > self.n:
return Partitions_n.cardinality(self)
return ZZ.sum(1 for x in self)
|
[
"def",
"cardinality",
"(",
"self",
")",
":",
"if",
"self",
".",
"_ell",
">",
"self",
".",
"n",
":",
"return",
"Partitions_n",
".",
"cardinality",
"(",
"self",
")",
"return",
"ZZ",
".",
"sum",
"(",
"1",
"for",
"x",
"in",
"self",
")"
] |
https://github.com/sagemath/sage/blob/f9b2db94f675ff16963ccdefba4f1a3393b3fe0d/src/sage/combinat/partition.py#L8005-L8040
|
|
rizar/attention-lvcsr
|
1ae52cafdd8419874846f9544a299eef9c758f3b
|
libs/Theano/theano/compile/mode.py
|
python
|
register_optimizer
|
(name, opt)
|
Add a `Optimizer` which can be referred to by `name` in `Mode`.
|
Add a `Optimizer` which can be referred to by `name` in `Mode`.
|
[
"Add",
"a",
"Optimizer",
"which",
"can",
"be",
"referred",
"to",
"by",
"name",
"in",
"Mode",
"."
] |
def register_optimizer(name, opt):
"""Add a `Optimizer` which can be referred to by `name` in `Mode`."""
if name in predefined_optimizers:
raise ValueError('Optimizer name already taken: %s' % name)
predefined_optimizers[name] = opt
|
[
"def",
"register_optimizer",
"(",
"name",
",",
"opt",
")",
":",
"if",
"name",
"in",
"predefined_optimizers",
":",
"raise",
"ValueError",
"(",
"'Optimizer name already taken: %s'",
"%",
"name",
")",
"predefined_optimizers",
"[",
"name",
"]",
"=",
"opt"
] |
https://github.com/rizar/attention-lvcsr/blob/1ae52cafdd8419874846f9544a299eef9c758f3b/libs/Theano/theano/compile/mode.py#L109-L113
|
||
Podshot/MCEdit-Unified
|
90abfb170c65b877ac67193e717fa3a3ded635dd
|
pymclevel/infiniteworld.py
|
python
|
MCInfdevOldLevel.close
|
(self)
|
Unload all chunks and close all open filehandles. Discard any unsaved data.
|
Unload all chunks and close all open filehandles. Discard any unsaved data.
|
[
"Unload",
"all",
"chunks",
"and",
"close",
"all",
"open",
"filehandles",
".",
"Discard",
"any",
"unsaved",
"data",
"."
] |
def close(self):
"""
Unload all chunks and close all open filehandles. Discard any unsaved data.
"""
self.unload()
try:
self.checkSessionLock()
shutil.rmtree(self.unsavedWorkFolder.filename, True)
shutil.rmtree(self.fileEditsFolder.filename, True)
except SessionLockLost:
pass
|
[
"def",
"close",
"(",
"self",
")",
":",
"self",
".",
"unload",
"(",
")",
"try",
":",
"self",
".",
"checkSessionLock",
"(",
")",
"shutil",
".",
"rmtree",
"(",
"self",
".",
"unsavedWorkFolder",
".",
"filename",
",",
"True",
")",
"shutil",
".",
"rmtree",
"(",
"self",
".",
"fileEditsFolder",
".",
"filename",
",",
"True",
")",
"except",
"SessionLockLost",
":",
"pass"
] |
https://github.com/Podshot/MCEdit-Unified/blob/90abfb170c65b877ac67193e717fa3a3ded635dd/pymclevel/infiniteworld.py#L1351-L1361
|
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