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HCIILAB/DeRPN | 21e6738ee1f7d3f159ee48d435c543e773f8ce99 | caffe/examples/pycaffe/layers/pascal_multilabel_datalayers.py | python | BatchLoader.load_next_image | (self) | return self.transformer.preprocess(im), multilabel | Load the next image in a batch. | Load the next image in a batch. | [
"Load",
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"next",
"image",
"in",
"a",
"batch",
"."
] | def load_next_image(self):
"""
Load the next image in a batch.
"""
# Did we finish an epoch?
if self._cur == len(self.indexlist):
self._cur = 0
shuffle(self.indexlist)
# Load an image
index = self.indexlist[self._cur] # Get the image index
image_file_name = index + '.jpg'
im = np.asarray(Image.open(
osp.join(self.pascal_root, 'JPEGImages', image_file_name)))
im = scipy.misc.imresize(im, self.im_shape) # resize
# do a simple horizontal flip as data augmentation
flip = np.random.choice(2)*2-1
im = im[:, ::flip, :]
# Load and prepare ground truth
multilabel = np.zeros(20).astype(np.float32)
anns = load_pascal_annotation(index, self.pascal_root)
for label in anns['gt_classes']:
# in the multilabel problem we don't care how MANY instances
# there are of each class. Only if they are present.
# The "-1" is b/c we are not interested in the background
# class.
multilabel[label - 1] = 1
self._cur += 1
return self.transformer.preprocess(im), multilabel | [
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orbingol/NURBS-Python | 8ae8b127eb0b130a25a6c81e98e90f319733bca0 | geomdl/visualization/VisVTK.py | python | VisConfig.__init__ | (self, **kwargs) | [] | def __init__(self, **kwargs):
super(VisConfig, self).__init__(**kwargs)
self._bg = ( # background colors
(0.5, 0.5, 0.5), (0.2, 0.2, 0.2), (0.25, 0.5, 0.75), (1.0, 1.0, 0.0),
(1.0, 0.5, 0.0), (0.5, 0.0, 1.0), (0.0, 0.0, 0.0), (1.0, 1.0, 1.0)
)
self._bg_id = 0 # used for keeping track of the background numbering
self.display_ctrlpts = kwargs.get('ctrlpts', True)
self.display_evalpts = kwargs.get('evalpts', True)
self.display_bbox = kwargs.get('bbox', False)
self.display_trims = kwargs.get('trims', True)
self.trim_size = kwargs.get('trim_size', 4)
self.figure_size = kwargs.get('figure_size', (800, 600)) # size of the render window
self.line_width = kwargs.get('line_width', 1.0)
self.figure_image_filename = "temp-figure.png" | [
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dingmyu/D4LCN | 9258bfb31376b97ab16abee31bd0fec131236c7a | models/resnet.py | python | resnet101 | (pretrained=False, **kwargs) | return model | Constructs a ResNet-101 model.
Args:
pretrained (bool): If True, returns a model pre-trained on ImageNet | Constructs a ResNet-101 model.
Args:
pretrained (bool): If True, returns a model pre-trained on ImageNet | [
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"""Constructs a ResNet-101 model.
Args:
pretrained (bool): If True, returns a model pre-trained on ImageNet
"""
model = ResNet(Bottleneck, [3, 4, 23, 3], **kwargs)
if pretrained:
model.load_state_dict(model_zoo.load_url(model_urls['resnet101']), strict=False)
return model | [
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caiiiac/Machine-Learning-with-Python | 1a26c4467da41ca4ebc3d5bd789ea942ef79422f | MachineLearning/venv/lib/python3.5/site-packages/pandas/core/indexes/base.py | python | Index._assert_can_do_op | (self, value) | Check value is valid for scalar op | Check value is valid for scalar op | [
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""" Check value is valid for scalar op """
if not lib.isscalar(value):
msg = "'value' must be a scalar, passed: {0}"
raise TypeError(msg.format(type(value).__name__)) | [
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crdoconnor/strictyaml | b456066a763285532fd75cd274d4a275d8499d6c | hitch/key.py | python | reformat | () | Reformat using black and then relint. | Reformat using black and then relint. | [
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"""
Reformat using black and then relint.
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pyfa-org/Pyfa | feaa52c36beeda21ab380fc74d8f871b81d49729 | gui/setEditor.py | python | ImplantSetEditor.exportPatterns | (self, event) | Event fired when export to clipboard button is clicked | Event fired when export to clipboard button is clicked | [
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"""Event fired when export to clipboard button is clicked"""
sIS = ImplantSets.getInstance()
toClipboard(sIS.exportSets())
self.stNotice.SetLabel(_t("Sets exported to clipboard")) | [
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/lib/python2.7/site-packages/setuptools/_vendor/pyparsing.py | python | lineno | (loc,strg) | return strg.count("\n",0,loc) + 1 | Returns current line number within a string, counting newlines as line separators.
The first line is number 1.
Note: the default parsing behavior is to expand tabs in the input string
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"""Returns current line number within a string, counting newlines as line separators.
The first line is number 1.
Note: the default parsing behavior is to expand tabs in the input string
before starting the parsing process. See L{I{ParserElement.parseString}<ParserElement.parseString>} for more information
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huggingface/transformers | 623b4f7c63f60cce917677ee704d6c93ee960b4b | src/transformers/utils/dummy_pytorch_quantization_and_torch_objects.py | python | QDQBertForTokenClassification.from_pretrained | (cls, *args, **kwargs) | [] | def from_pretrained(cls, *args, **kwargs):
requires_backends(cls, ["pytorch_quantization", "torch"]) | [
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/lib/python2.7/site-packages/attr/_make.py | python | _CountingAttr.__init__ | (self, default, validator, repr, cmp, hash, init, converter,
metadata, type) | [] | def __init__(self, default, validator, repr, cmp, hash, init, converter,
metadata, type):
_CountingAttr.cls_counter += 1
self.counter = _CountingAttr.cls_counter
self._default = default
# If validator is a list/tuple, wrap it using helper validator.
if validator and isinstance(validator, (list, tuple)):
self._validator = and_(*validator)
else:
self._validator = validator
self.repr = repr
self.cmp = cmp
self.hash = hash
self.init = init
self.converter = converter
self.metadata = metadata
self.type = type | [
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dropbox/dropbox-sdk-python | 015437429be224732990041164a21a0501235db1 | dropbox/team_log.py | python | EventDetails.is_shared_link_remove_expiry_details | (self) | return self._tag == 'shared_link_remove_expiry_details' | Check if the union tag is ``shared_link_remove_expiry_details``.
:rtype: bool | Check if the union tag is ``shared_link_remove_expiry_details``. | [
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] | def is_shared_link_remove_expiry_details(self):
"""
Check if the union tag is ``shared_link_remove_expiry_details``.
:rtype: bool
"""
return self._tag == 'shared_link_remove_expiry_details' | [
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AppScale/gts | 46f909cf5dc5ba81faf9d81dc9af598dcf8a82a9 | AppServer/google/appengine/ext/mapreduce/base_handler.py | python | TaskQueueHandler.task_retry_count | (self) | return int(self.request.headers.get("X-AppEngine-TaskExecutionCount", 0)) | Number of times this task has been retried. | Number of times this task has been retried. | [
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] | def task_retry_count(self):
"""Number of times this task has been retried."""
return int(self.request.headers.get("X-AppEngine-TaskExecutionCount", 0)) | [
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crossbario/autobahn-python | fa9f2da0c5005574e63456a3a04f00e405744014 | autobahn/wamp/auth.py | python | derive_scram_credential | (email: str, password: str, salt: Optional[bytes] = None) | return credential | Derive WAMP-SCRAM credentials from user email and password. The SCRAM parameters used
are the following (these are also contained in the returned credentials):
* kdf ``argon2id-13``
* time cost ``4096``
* memory cost ``512``
* parallelism ``1``
See `draft-irtf-cfrg-argon2 <https://datatracker.ietf.org/doc/draft-irtf-cfrg-argon2/>`__ and
`argon2-cffi <https://argon2-cffi.readthedocs.io/en/stable/>`__.
:param email: User email.
:param password: User password.
:param salt: Optional salt to use (must be 16 bytes long). If none is given, compute salt
from email as ``salt = SHA256(email)[:16]``.
:return: WAMP-SCRAM credentials. When serialized, the returned credentials can be copy-pasted
into the ``config.json`` node configuration for a Crossbar.io node. | Derive WAMP-SCRAM credentials from user email and password. The SCRAM parameters used
are the following (these are also contained in the returned credentials): | [
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"""
Derive WAMP-SCRAM credentials from user email and password. The SCRAM parameters used
are the following (these are also contained in the returned credentials):
* kdf ``argon2id-13``
* time cost ``4096``
* memory cost ``512``
* parallelism ``1``
See `draft-irtf-cfrg-argon2 <https://datatracker.ietf.org/doc/draft-irtf-cfrg-argon2/>`__ and
`argon2-cffi <https://argon2-cffi.readthedocs.io/en/stable/>`__.
:param email: User email.
:param password: User password.
:param salt: Optional salt to use (must be 16 bytes long). If none is given, compute salt
from email as ``salt = SHA256(email)[:16]``.
:return: WAMP-SCRAM credentials. When serialized, the returned credentials can be copy-pasted
into the ``config.json`` node configuration for a Crossbar.io node.
"""
assert HAS_ARGON, 'missing dependency argon2'
from argon2.low_level import hash_secret
from argon2.low_level import Type
# derive salt from email
if not salt:
m = hashlib.sha256()
m.update(email.encode('utf8'))
salt = m.digest()[:16]
assert len(salt) == 16
hash_data = hash_secret(
secret=password.encode('utf8'),
salt=salt,
time_cost=4096,
memory_cost=512,
parallelism=1,
hash_len=32,
type=Type.ID,
version=19,
)
_, tag, v, params, _, salted_password = hash_data.decode('ascii').split('$')
assert tag == 'argon2id'
assert v == 'v=19' # argon's version 1.3 is represented as 0x13, which is 19 decimal...
params = {
k: v
for k, v in
[x.split('=') for x in params.split(',')]
}
salted_password = salted_password.encode('ascii')
client_key = hmac.new(salted_password, b"Client Key", hashlib.sha256).digest()
stored_key = hashlib.new('sha256', client_key).digest()
server_key = hmac.new(salted_password, b"Server Key", hashlib.sha256).digest()
credential = {
"kdf": "argon2id-13",
"memory": int(params['m']),
"iterations": int(params['t']),
"salt": binascii.b2a_hex(salt).decode('ascii'),
"stored-key": binascii.b2a_hex(stored_key).decode('ascii'),
"server-key": binascii.b2a_hex(server_key).decode('ascii'),
}
return credential | [
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smicallef/spiderfoot | fd4bf9394c9ab3ecc90adc3115c56349fb23165b | modules/sfp_dns_for_family.py | python | sfp_dns_for_family.setup | (self, sfc, userOpts=dict()) | [] | def setup(self, sfc, userOpts=dict()):
self.sf = sfc
self.results = self.tempStorage()
for opt in list(userOpts.keys()):
self.opts[opt] = userOpts[opt] | [
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aaPanel/BaoTa | 9bb1336f31ae2893ab513af7a3efed633338c64b | class/ssh_terminal.py | python | ssh_terminal.history_send | (self,send_data) | @name 从发送实体保存命令
@author hwliang<2020-08-12>
@param send_data<string> 数据实体
@return void | [] | def history_send(self,send_data):
'''
@name 从发送实体保存命令
@author hwliang<2020-08-12>
@param send_data<string> 数据实体
@return void
'''
if not send_data: return
his_path = self._save_path + self._host
if not os.path.exists(his_path): return
his_file = his_path + '/history.pl'
#上下切换命令
if send_data in ["\x1b[A","\x1b[B"]:
self._last_cmd_tip = 2
return
#左移光标
if send_data in ["\x1b[C"]:
self._last_num -= 1
return
# 右移光标
if send_data in ["\x1b[D"]:
self._last_num += 1
return
#退格
if send_data == "\x7f":
self._last_cmd = self._last_cmd[:-1]
return
#过滤特殊符号
if send_data in ["\x1b[C","\x1b[D","\x1b[K","\x07","\x08","\x03","\x01","\x02","\x04","\x05","\x06","\x1bOB","\x1bOA","\x1b[8P","\x1b","\x1b[4P","\x1b[6P","\x1b[5P"]:
return
#Tab补全处理
if send_data == "\t":
self._last_cmd_tip = 1
return
if str(send_data).find("\x1b") != -1:
return
if send_data[-1] in ['\r','\n']:
if not self._last_cmd: return
his_shell = [int(time.time()),self._client,self._user,self._last_cmd]
public.writeFile(his_file, json.dumps(his_shell) + "\n","a+")
self._last_cmd = ""
#超过50M则保留最新的20000行
if os.stat(his_file).st_size > 52428800:
his_tmp = public.GetNumLines(his_file,20000)
public.writeFile(his_file, his_tmp)
else:
if self._last_num >= 0:
self._last_cmd += send_data
else:
self._last_cmd.insert(len(self._last_cmd) + self._last_num, send_data) | [
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pymedusa/Medusa | 1405fbb6eb8ef4d20fcca24c32ddca52b11f0f38 | medusa/databases/main_db.py | python | AddManualSearched.test | (self) | return self.connection.version >= (44, 3) | Test if the version is < 44.3 | Test if the version is < 44.3 | [
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custom-components/ble_monitor | 64f9cb064781c6ddc5089657d3710b31d10fe1ba | custom_components/ble_monitor/__init__.py | python | BLEmonitor.__init__ | (self, config) | Init. | Init. | [
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] | def __init__(self, config):
"""Init."""
self.dataqueue = {
"binary": janus.Queue(),
"measuring": janus.Queue(),
"tracker": janus.Queue(),
}
self.config = config
self.dumpthread = None | [
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mesalock-linux/mesapy | ed546d59a21b36feb93e2309d5c6b75aa0ad95c9 | pypy/module/imp/__init__.py | python | Module.__init__ | (self, space, *args) | NOT_RPYTHON | NOT_RPYTHON | [
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add_fork_hook('parent', interp_imp.release_lock)
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angr/angr | 4b04d56ace135018083d36d9083805be8146688b | angr/engines/pcode/behavior.py | python | OpBehaviorIntOr.__init__ | (self) | [] | def __init__(self):
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jcartledge/sublime-worksheet | 44b2ba96d02759b485adbf85c1a2c9d45cc39599 | repl/ftfy/__init__.py | python | fix_text_segment | (text, normalization='NFKC', entities=True) | return text | Apply fixes to text in a single chunk. This could be a line of text
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within a larger run of `fix_text`, or it could be a larger amount
of text that you are certain is all in the same encoding.
"""
if isinstance(text, bytes):
raise UnicodeError(BYTES_ERROR_TEXT)
text = remove_terminal_escapes(text)
if entities:
text = unescape_html(text)
text = fix_bad_encoding(text)
text = text.translate(CONTROL_CHARS)
if normalization is not None:
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text = uncurl_quotes(text)
text = remove_bom(text)
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/Python-2.7.9/Lib/wave.py | python | Wave_write.__del__ | (self) | [] | def __del__(self):
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WerWolv/EdiZon_CheatsConfigsAndScripts | d16d36c7509c01dca770f402babd83ff2e9ae6e7 | Scripts/lib/python3.5/imaplib.py | python | IMAP4.partial | (self, message_num, message_part, start, length) | return self._untagged_response(typ, dat, 'FETCH') | Fetch truncated part of a message.
(typ, [data, ...]) = <instance>.partial(message_num, message_part, start, length)
'data' is tuple of message part envelope and data. | Fetch truncated part of a message. | [
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"""Fetch truncated part of a message.
(typ, [data, ...]) = <instance>.partial(message_num, message_part, start, length)
'data' is tuple of message part envelope and data.
"""
name = 'PARTIAL'
typ, dat = self._simple_command(name, message_num, message_part, start, length)
return self._untagged_response(typ, dat, 'FETCH') | [
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autonomousvision/occupancy_networks | 406f79468fb8b57b3e76816aaa73b1915c53ad22 | im2mesh/common.py | python | get_camera_args | (data, loc_field=None, scale_field=None, device=None) | return kwargs | Returns dictionary of camera arguments.
Args:
data (dict): data dictionary
loc_field (str): name of location field
scale_field (str): name of scale field
device (device): pytorch device | Returns dictionary of camera arguments. | [
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''' Returns dictionary of camera arguments.
Args:
data (dict): data dictionary
loc_field (str): name of location field
scale_field (str): name of scale field
device (device): pytorch device
'''
Rt = data['inputs.world_mat'].to(device)
K = data['inputs.camera_mat'].to(device)
if loc_field is not None:
loc = data[loc_field].to(device)
else:
loc = torch.zeros(K.size(0), 3, device=K.device, dtype=K.dtype)
if scale_field is not None:
scale = data[scale_field].to(device)
else:
scale = torch.zeros(K.size(0), device=K.device, dtype=K.dtype)
Rt = fix_Rt_camera(Rt, loc, scale)
K = fix_K_camera(K, img_size=137.)
kwargs = {'Rt': Rt, 'K': K}
return kwargs | [
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PythonOT/POT | be0ed1dcd0b65ec804e454f1a2d3c0d227c0ddbe | ot/backend.py | python | Backend.repeat | (self, a, repeats, axis=None) | r"""
Repeats elements of a tensor.
This function follows the api from :any:`numpy.repeat`
See: https://numpy.org/doc/stable/reference/generated/numpy.repeat.html | r"""
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r"""
Repeats elements of a tensor.
This function follows the api from :any:`numpy.repeat`
See: https://numpy.org/doc/stable/reference/generated/numpy.repeat.html
"""
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pyga/parsley | c89b3f0e09a9501f285a14ae446a77a56ee99942 | ometa/interp.py | python | TrampolinedGrammarInterpreter.parse_Exactly | (self, spec) | Accept a one or more characters that equal the given spec. | Accept a one or more characters that equal the given spec. | [
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Accept a one or more characters that equal the given spec.
"""
wanted = spec.data
result = []
for c in wanted:
try:
val, p = self.input.head()
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yield _feed_me
val, p = self.input.head()
result.append(val)
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self.input = self.input.tail()
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raise self.err(p.withMessage(expected(None, wanted)))
yield ''.join(result), p | [
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tav/pylibs | 3c16b843681f54130ee6a022275289cadb2f2a69 | paramiko/transport.py | python | Transport.getpeername | (self) | return gp() | Return the address of the remote side of this Transport, if possible.
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clinton-hall/nzbToMedia | 27669389216902d1085660167e7bda0bd8527ecf | libs/win/six.py | python | add_metaclass | (metaclass) | return wrapper | Class decorator for creating a class with a metaclass. | Class decorator for creating a class with a metaclass. | [
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"""Class decorator for creating a class with a metaclass."""
def wrapper(cls):
orig_vars = cls.__dict__.copy()
slots = orig_vars.get('__slots__')
if slots is not None:
if isinstance(slots, str):
slots = [slots]
for slots_var in slots:
orig_vars.pop(slots_var)
orig_vars.pop('__dict__', None)
orig_vars.pop('__weakref__', None)
if hasattr(cls, '__qualname__'):
orig_vars['__qualname__'] = cls.__qualname__
return metaclass(cls.__name__, cls.__bases__, orig_vars)
return wrapper | [
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cloudera/hue | 23f02102d4547c17c32bd5ea0eb24e9eadd657a4 | desktop/core/ext-py/zope.interface-4.5.0/src/zope/interface/declarations.py | python | classImplements | (cls, *interfaces) | Declare additional interfaces implemented for instances of a class
The arguments after the class are one or more interfaces or
interface specifications (``IDeclaration`` objects).
The interfaces given (including the interfaces in the specifications)
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"""Declare additional interfaces implemented for instances of a class
The arguments after the class are one or more interfaces or
interface specifications (``IDeclaration`` objects).
The interfaces given (including the interfaces in the specifications)
are added to any interfaces previously declared.
"""
spec = implementedBy(cls)
spec.declared += tuple(_normalizeargs(interfaces))
# compute the bases
bases = []
seen = {}
for b in spec.declared:
if b not in seen:
seen[b] = 1
bases.append(b)
if spec.inherit is not None:
for c in spec.inherit.__bases__:
b = implementedBy(c)
if b not in seen:
seen[b] = 1
bases.append(b)
spec.__bases__ = tuple(bases) | [
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DataDog/integrations-core | 934674b29d94b70ccc008f76ea172d0cdae05e1e | sonarqube/datadog_checks/sonarqube/config_models/defaults.py | python | instance_timeout | (field, value) | return 10 | [] | def instance_timeout(field, value):
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ztosec/hunter | 4ee5cca8dc5fc5d7e631e935517bd0f493c30a37 | SqlmapCelery/sqlmap/lib/request/basic.py | python | checkCharEncoding | (encoding, warn=True) | return encoding | Checks encoding name, repairs common misspellings and adjusts to
proper namings used in codecs module
>>> checkCharEncoding('iso-8858', False)
'iso8859-1'
>>> checkCharEncoding('en_us', False)
'utf8' | Checks encoding name, repairs common misspellings and adjusts to
proper namings used in codecs module | [
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"""
Checks encoding name, repairs common misspellings and adjusts to
proper namings used in codecs module
>>> checkCharEncoding('iso-8858', False)
'iso8859-1'
>>> checkCharEncoding('en_us', False)
'utf8'
"""
if encoding:
encoding = encoding.lower()
else:
return encoding
# Reference: http://www.destructor.de/charsets/index.htm
translate = {"windows-874": "iso-8859-11", "utf-8859-1": "utf8", "en_us": "utf8", "macintosh": "iso-8859-1", "euc_tw": "big5_tw", "th": "tis-620", "unicode": "utf8", "utc8": "utf8", "ebcdic": "ebcdic-cp-be", "iso-8859": "iso8859-1", "ansi": "ascii", "gbk2312": "gbk", "windows-31j": "cp932", "en": "us"}
for delimiter in (';', ',', '('):
if delimiter in encoding:
encoding = encoding[:encoding.find(delimiter)].strip()
encoding = encoding.replace(""", "")
# popular typos/errors
if "8858" in encoding:
encoding = encoding.replace("8858", "8859") # iso-8858 -> iso-8859
elif "8559" in encoding:
encoding = encoding.replace("8559", "8859") # iso-8559 -> iso-8859
elif "8895" in encoding:
encoding = encoding.replace("8895", "8859") # iso-8895 -> iso-8859
elif "5889" in encoding:
encoding = encoding.replace("5889", "8859") # iso-5889 -> iso-8859
elif "5589" in encoding:
encoding = encoding.replace("5589", "8859") # iso-5589 -> iso-8859
elif "2313" in encoding:
encoding = encoding.replace("2313", "2312") # gb2313 -> gb2312
elif encoding.startswith("x-"):
encoding = encoding[len("x-"):] # x-euc-kr -> euc-kr / x-mac-turkish -> mac-turkish
elif "windows-cp" in encoding:
encoding = encoding.replace("windows-cp", "windows") # windows-cp-1254 -> windows-1254
# name adjustment for compatibility
if encoding.startswith("8859"):
encoding = "iso-%s" % encoding
elif encoding.startswith("cp-"):
encoding = "cp%s" % encoding[3:]
elif encoding.startswith("euc-"):
encoding = "euc_%s" % encoding[4:]
elif encoding.startswith("windows") and not encoding.startswith("windows-"):
encoding = "windows-%s" % encoding[7:]
elif encoding.find("iso-88") > 0:
encoding = encoding[encoding.find("iso-88"):]
elif encoding.startswith("is0-"):
encoding = "iso%s" % encoding[4:]
elif encoding.find("ascii") > 0:
encoding = "ascii"
elif encoding.find("utf8") > 0:
encoding = "utf8"
elif encoding.find("utf-8") > 0:
encoding = "utf-8"
# Reference: http://philip.html5.org/data/charsets-2.html
if encoding in translate:
encoding = translate[encoding]
elif encoding in ("null", "{charset}", "charset", "*") or not re.search(r"\w", encoding):
return None
# Reference: http://www.iana.org/assignments/character-sets
# Reference: http://docs.python.org/library/codecs.html
try:
codecs.lookup(encoding.encode(UNICODE_ENCODING) if isinstance(encoding, unicode) else encoding)
except (LookupError, ValueError):
if warn:
warnMsg = "unknown web page charset '%s'. " % encoding
warnMsg += "Please report by e-mail to 'dev@sqlmap.org'"
singleTimeLogMessage(warnMsg, logging.WARN, encoding)
encoding = None
if encoding:
try:
unicode(randomStr(), encoding)
except:
if warn:
warnMsg = "invalid web page charset '%s'" % encoding
singleTimeLogMessage(warnMsg, logging.WARN, encoding)
encoding = None
return encoding | [
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beeware/colosseum | cbf974be54fd7f6fddbe7285704cfaf7a866c5c5 | src/colosseum/dimensions.py | python | Size.ratio | (self) | return self._ratio | [] | def ratio(self):
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pascalw/Airplayer | cb6f6a393710a31f934e3c09de4f689158d23b50 | airplayer/lib/jsonrpclib/jsonrpc.py | python | Payload.request | (self, method, params=[]) | return request | [] | def request(self, method, params=[]):
if type(method) not in types.StringTypes:
raise ValueError('Method name must be a string.')
if not self.id:
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request = { 'id':self.id, 'method':method }
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PlasmaPy/PlasmaPy | 78d63e341216475ce3318e1409296480407c9019 | plasmapy/diagnostics/langmuir.py | python | _fit_func_lin | (x, x0, y0, c0) | return y0 + c0 * (x - x0) | r"""Linear fitting function. | r"""Linear fitting function. | [
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Jenyay/outwiker | 50530cf7b3f71480bb075b2829bc0669773b835b | plugins/webpage/webpage/libs/email/_header_value_parser.py | python | get_dot_atom | (value) | return dot_atom, value | dot-atom = [CFWS] dot-atom-text [CFWS]
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word. | dot-atom = [CFWS] dot-atom-text [CFWS] | [
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""" dot-atom = [CFWS] dot-atom-text [CFWS]
Any place we can have a dot atom, we could instead have an rfc2047 encoded
word.
"""
dot_atom = DotAtom()
if value[0] in CFWS_LEADER:
token, value = get_cfws(value)
dot_atom.append(token)
if value.startswith('=?'):
try:
token, value = get_encoded_word(value)
except errors.HeaderParseError:
# XXX: need to figure out how to register defects when
# appropriate here.
token, value = get_dot_atom_text(value)
else:
token, value = get_dot_atom_text(value)
dot_atom.append(token)
if value and value[0] in CFWS_LEADER:
token, value = get_cfws(value)
dot_atom.append(token)
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dpgaspar/Flask-AppBuilder | 557249f33b66d02a48c1322ef21324b815abe18e | flask_appbuilder/validators.py | python | default_password_complexity | (password: str) | FAB's default password complexity validator, set FAB_PASSWORD_COMPLEXITY_ENABLED
to True to enable it | FAB's default password complexity validator, set FAB_PASSWORD_COMPLEXITY_ENABLED
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"""
FAB's default password complexity validator, set FAB_PASSWORD_COMPLEXITY_ENABLED
to True to enable it
"""
match = re.search(password_complexity_regex, password)
if not match:
raise PasswordComplexityValidationError(
gettext(
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oilshell/oil | 94388e7d44a9ad879b12615f6203b38596b5a2d3 | Python-2.7.13/Lib/plat-mac/PixMapWrapper.py | python | PixMapWrapper._unstuff | (self, element) | return struct.unpack(fmt, self._header[offset:offset+struct.calcsize(fmt)])[0] | [] | def _unstuff(self, element):
offset = _pmElemOffset[element]
fmt = _pmElemFormat[element]
return struct.unpack(fmt, self._header[offset:offset+struct.calcsize(fmt)])[0] | [
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larryhastings/gilectomy | 4315ec3f1d6d4f813cc82ce27a24e7f784dbfc1a | Lib/asyncio/tasks.py | python | Task.current_task | (cls, loop=None) | return cls._current_tasks.get(loop) | Return the currently running task in an event loop or None.
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"""Return the currently running task in an event loop or None.
By default the current task for the current event loop is returned.
None is returned when called not in the context of a Task.
"""
if loop is None:
loop = events.get_event_loop()
return cls._current_tasks.get(loop) | [
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sametmax/Django--an-app-at-a-time | 99eddf12ead76e6dfbeb09ce0bae61e282e22f8a | ignore_this_directory/django/contrib/admin/options.py | python | ModelAdmin.response_delete | (self, request, obj_display, obj_id) | return HttpResponseRedirect(post_url) | Determine the HttpResponse for the delete_view stage. | Determine the HttpResponse for the delete_view stage. | [
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"""
opts = self.model._meta
if IS_POPUP_VAR in request.POST:
popup_response_data = json.dumps({
'action': 'delete',
'value': str(obj_id),
})
return TemplateResponse(request, self.popup_response_template or [
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'admin/popup_response.html',
], {
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})
self.message_user(
request,
_('The %(name)s "%(obj)s" was deleted successfully.') % {
'name': opts.verbose_name,
'obj': obj_display,
},
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if self.has_change_permission(request, None):
post_url = reverse(
'admin:%s_%s_changelist' % (opts.app_label, opts.model_name),
current_app=self.admin_site.name,
)
preserved_filters = self.get_preserved_filters(request)
post_url = add_preserved_filters(
{'preserved_filters': preserved_filters, 'opts': opts}, post_url
)
else:
post_url = reverse('admin:index', current_app=self.admin_site.name)
return HttpResponseRedirect(post_url) | [
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zzzeek/sqlalchemy | fc5c54fcd4d868c2a4c7ac19668d72f506fe821e | lib/sqlalchemy/engine/interfaces.py | python | Connectable.execute | (self, object_, *multiparams, **params) | Executes the given construct and returns a
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yt-project/yt | dc7b24f9b266703db4c843e329c6c8644d47b824 | yt/visualization/volume_rendering/scene.py | python | Scene.__init__ | (self) | r"""Create a new Scene instance | r"""Create a new Scene instance | [
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self._last_render = None
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catap/namebench | 9913a7a1a7955a3759eb18cbe73b421441a7a00f | nb_third_party/jinja2/filters.py | python | do_int | (value, default=0) | Convert the value into an integer. If the
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except (TypeError, ValueError):
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paulvangentcom/python_corona_simulation | a5dddd3e13d2bb768a9294d85ab27329be9a21dd | old/simple_simulation.py | python | infect | (population, infection_range, infection_chance, frame) | return population | finds new infections
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Keyword arguments
----------------- | [
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'''finds new infections
Keyword arguments
-----------------
'''
#find new infections
infected_previous_step = population[population[:,6] == 1]
new_infections = []
#if less than half are infected, slice based on infected (to speed up computation)
if len(infected_previous_step) < (pop_size // 2):
for patient in infected_previous_step:
#define infection zone for patient
infection_zone = [patient[1] - infection_range, patient[2] - infection_range,
patient[1] + infection_range, patient[2] + infection_range]
#find healthy people surrounding infected patient
indices = np.int32(population[:,0][(infection_zone[0] < population[:,1]) &
(population[:,1] < infection_zone[2]) &
(infection_zone[1] < population [:,2]) &
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for idx in indices:
#roll die to see if healthy person will be infected
if np.random.random() < infection_chance:
population[idx][6] = 1
population[idx][8] = frame
new_infections.append(idx)
else:
#if more than half are infected slice based in healthy people (to speed up computation)
healthy_previous_step = population[population[:,6] == 0]
sick_previous_step = population[population[:,6] == 1]
for person in healthy_previous_step:
#define infecftion range around healthy person
infection_zone = [person[1] - infection_range, person[2] - infection_range,
person[1] + infection_range, person[2] + infection_range]
if person[6] == 0: #if person is not already infected, find if infected are nearby
#find infected nearby healthy person
poplen = len(sick_previous_step[:,6][(infection_zone[0] < sick_previous_step[:,1]) &
(sick_previous_step[:,1] < infection_zone[2]) &
(infection_zone[1] < sick_previous_step [:,2]) &
(sick_previous_step[:,2] < infection_zone[3]) &
(sick_previous_step[:,6] == 1)])
if poplen > 0:
if np.random.random() < (infection_chance * poplen):
#roll die to see if healthy person will be infected
population[np.int32(person[0])][6] = 1
population[np.int32(person[0])][8] = frame
new_infections.append(np.int32(person[0]))
if len(new_infections) > 0:
print('at timestep %i these people got sick: %s' %(frame, new_infections))
return population | [
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omz/PythonistaAppTemplate | f560f93f8876d82a21d108977f90583df08d55af | PythonistaAppTemplate/PythonistaKit.framework/pylib/site-packages/flask/helpers.py | python | find_package | (import_name) | return None, package_path | Finds a package and returns the prefix (or None if the package is
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root_mod_name = import_name.split('.')[0]
loader = pkgutil.get_loader(root_mod_name)
if loader is None or import_name == '__main__':
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package_path = os.getcwd()
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ajinabraham/OWASP-Xenotix-XSS-Exploit-Framework | cb692f527e4e819b6c228187c5702d990a180043 | external/Scripting Engine/Xenotix Python Scripting Engine/bin/x86/Debug/Lib/runpy.py | python | _run_module_code | (code, init_globals=None,
mod_name=None, mod_fname=None,
mod_loader=None, pkg_name=None) | return mod_globals.copy() | Helper to run code in new namespace with sys modified | Helper to run code in new namespace with sys modified | [
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] | def _run_module_code(code, init_globals=None,
mod_name=None, mod_fname=None,
mod_loader=None, pkg_name=None):
"""Helper to run code in new namespace with sys modified"""
with _TempModule(mod_name) as temp_module, _ModifiedArgv0(mod_fname):
mod_globals = temp_module.module.__dict__
_run_code(code, mod_globals, init_globals,
mod_name, mod_fname, mod_loader, pkg_name)
# Copy the globals of the temporary module, as they
# may be cleared when the temporary module goes away
return mod_globals.copy() | [
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mithril-global/GoAgentX | 788fbd5e1c824c75cf98a9aef8a6d4ec8df25e95 | GoAgentX.app/Contents/PlugIns/shadowsocks.gxbundle/Contents/Resources/bin/python/M2Crypto/ftpslib.py | python | FTP_TLS.auth_tls | (self) | Secure the control connection per AUTH TLS, aka AUTH TLS-C. | Secure the control connection per AUTH TLS, aka AUTH TLS-C. | [
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"""Secure the control connection per AUTH TLS, aka AUTH TLS-C."""
self.voidcmd('AUTH TLS')
s = SSL.Connection(self.ssl_ctx, self.sock)
s.setup_ssl()
s.set_connect_state()
s.connect_ssl()
self.sock = s
self.file = self.sock.makefile() | [
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sagemath/sage | f9b2db94f675ff16963ccdefba4f1a3393b3fe0d | src/sage/combinat/cluster_algebra_quiver/cluster_seed.py | python | ClusterSeed.mutation_class | (self, depth=infinity, show_depth=False, return_paths=False,
up_to_equivalence=True, only_sink_source=False) | return list( S for S in self.mutation_class_iter( depth=depth, show_depth=show_depth, return_paths=return_paths, up_to_equivalence=up_to_equivalence, only_sink_source=only_sink_source ) ) | r"""
Return the mutation class of ``self`` with respect to
certain constraints.
.. NOTE::
Vertex labels are not tracked in this method.
.. SEEALSO::
:meth:`mutation_class_iter`
INPUT:
- ``depth`` -- (default: ``infinity`) integer, only seeds with
distance at most depth from ``self`` are returned
- ``show_depth`` -- (default: ``False``) if ``True``, the actual depth
of the mutation is shown
- ``return_paths`` -- (default: ``False``) if ``True``, a shortest
path of mutation sequences from self to the given quiver is
returned as well
- ``up_to_equivalence`` -- (default: ``True``) if ``True``, only
seeds up to equivalence are considered
- ``sink_source`` -- (default: ``False``) if ``True``, only mutations
at sinks and sources are applied
EXAMPLES:
- for examples see :meth:`mutation_class_iter`
TESTS::
sage: A = ClusterSeed(['A',3]).mutation_class() | r"""
Return the mutation class of ``self`` with respect to
certain constraints. | [
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up_to_equivalence=True, only_sink_source=False):
r"""
Return the mutation class of ``self`` with respect to
certain constraints.
.. NOTE::
Vertex labels are not tracked in this method.
.. SEEALSO::
:meth:`mutation_class_iter`
INPUT:
- ``depth`` -- (default: ``infinity`) integer, only seeds with
distance at most depth from ``self`` are returned
- ``show_depth`` -- (default: ``False``) if ``True``, the actual depth
of the mutation is shown
- ``return_paths`` -- (default: ``False``) if ``True``, a shortest
path of mutation sequences from self to the given quiver is
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- ``up_to_equivalence`` -- (default: ``True``) if ``True``, only
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- ``sink_source`` -- (default: ``False``) if ``True``, only mutations
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EXAMPLES:
- for examples see :meth:`mutation_class_iter`
TESTS::
sage: A = ClusterSeed(['A',3]).mutation_class()
"""
if depth is infinity and not self.is_finite():
raise ValueError('The mutation class can - for infinite types - only be computed up to a given depth')
return list( S for S in self.mutation_class_iter( depth=depth, show_depth=show_depth, return_paths=return_paths, up_to_equivalence=up_to_equivalence, only_sink_source=only_sink_source ) ) | [
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AppScale/gts | 46f909cf5dc5ba81faf9d81dc9af598dcf8a82a9 | AppServer/google/net/proto2/python/public/service.py | python | RpcController.NotifyOnCancel | (self, callback) | Sets a callback to invoke on cancel.
Asks that the given callback be called when the RPC is canceled. The
callback will always be called exactly once. If the RPC completes without
being canceled, the callback will be called after completion. If the RPC
has already been canceled when NotifyOnCancel() is called, the callback
will be called immediately.
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] | def NotifyOnCancel(self, callback):
"""Sets a callback to invoke on cancel.
Asks that the given callback be called when the RPC is canceled. The
callback will always be called exactly once. If the RPC completes without
being canceled, the callback will be called after completion. If the RPC
has already been canceled when NotifyOnCancel() is called, the callback
will be called immediately.
NotifyOnCancel() must be called no more than once per request.
"""
raise NotImplementedError | [
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catap/namebench | 9913a7a1a7955a3759eb18cbe73b421441a7a00f | libnamebench/geoip.py | python | GetInfoForCountry | (country_name_or_code) | Get code, name, lat and lon for a given country name or code. | Get code, name, lat and lon for a given country name or code. | [
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] | def GetInfoForCountry(country_name_or_code):
"""Get code, name, lat and lon for a given country name or code."""
match = False
partial_match = False
if not country_name_or_code:
return None
if len(country_name_or_code) == 2:
country_code = country_name_or_code.upper()
country_name = False
else:
country_name = country_name_or_code
country_code = False
for row in ReadCountryData():
lat, lon = row['coords'].split(',')
if country_code:
if row['code'] == country_code:
return row['code'], row['name'], lat, lon
elif country_name:
if re.match("^%s$" % country_name, row['name'], re.I):
return row['code'], row['name'], lat, lon
elif re.search('^%s \(' % country_name, row['name'], re.I):
return row['code'], row['name'], lat, lon
elif re.search('\(%s\)' % country_name, row['name'], re.I):
return row['code'], row['name'], lat, lon
elif re.match("^%s" % country_name, row['name'], re.I):
match = (row['code'], row['name'], lat, lon)
elif re.search(country_name, row['name'], re.I):
partial_match = (row['code'], row['name'], lat, lon)
if match:
print "Could not find explicit entry for '%s', good match: %s" % (country_name_or_code, match)
return match
elif partial_match:
print "Could not find explicit entry for '%s', partial match: %s" % (country_name_or_code, partial_match)
return partial_match
else:
print "'%s' does not match any countries in our list." % country_name_or_code
return (None, None, None, None) | [
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golismero/golismero | 7d605b937e241f51c1ca4f47b20f755eeefb9d76 | thirdparty_libs/nltk/sem/drt.py | python | DrsDrawer._get_centered_top | (self, top, full_height, item_height) | return top + (full_height - item_height) / 2 | Get the y-coordinate of the point that a figure should start at if
its height is 'item_height' and it needs to be centered in an area that
starts at 'top' and is 'full_height' tall. | Get the y-coordinate of the point that a figure should start at if
its height is 'item_height' and it needs to be centered in an area that
starts at 'top' and is 'full_height' tall. | [
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its height is 'item_height' and it needs to be centered in an area that
starts at 'top' and is 'full_height' tall."""
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triaquae/triaquae | bbabf736b3ba56a0c6498e7f04e16c13b8b8f2b9 | TriAquae/models/django/contrib/admin/templatetags/log.py | python | get_admin_log | (parser, token) | return AdminLogNode(limit=tokens[1], varname=tokens[3], user=(len(tokens) > 5 and tokens[5] or None)) | Populates a template variable with the admin log for the given criteria.
Usage::
{% get_admin_log [limit] as [varname] for_user [context_var_containing_user_obj] %}
Examples::
{% get_admin_log 10 as admin_log for_user 23 %}
{% get_admin_log 10 as admin_log for_user user %}
{% get_admin_log 10 as admin_log %}
Note that ``context_var_containing_user_obj`` can be a hard-coded integer
(user ID) or the name of a template context variable containing the user
object whose ID you want. | Populates a template variable with the admin log for the given criteria. | [
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] | def get_admin_log(parser, token):
"""
Populates a template variable with the admin log for the given criteria.
Usage::
{% get_admin_log [limit] as [varname] for_user [context_var_containing_user_obj] %}
Examples::
{% get_admin_log 10 as admin_log for_user 23 %}
{% get_admin_log 10 as admin_log for_user user %}
{% get_admin_log 10 as admin_log %}
Note that ``context_var_containing_user_obj`` can be a hard-coded integer
(user ID) or the name of a template context variable containing the user
object whose ID you want.
"""
tokens = token.contents.split()
if len(tokens) < 4:
raise template.TemplateSyntaxError(
"'get_admin_log' statements require two arguments")
if not tokens[1].isdigit():
raise template.TemplateSyntaxError(
"First argument to 'get_admin_log' must be an integer")
if tokens[2] != 'as':
raise template.TemplateSyntaxError(
"Second argument to 'get_admin_log' must be 'as'")
if len(tokens) > 4:
if tokens[4] != 'for_user':
raise template.TemplateSyntaxError(
"Fourth argument to 'get_admin_log' must be 'for_user'")
return AdminLogNode(limit=tokens[1], varname=tokens[3], user=(len(tokens) > 5 and tokens[5] or None)) | [
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LeGoffLoic/Nodz | 0ee255c62883f7a374a9de6cbcf555e3352e5dec | nodz_main.py | python | Nodz.mouseReleaseEvent | (self, event) | Apply tablet zoom, dragging and selection. | Apply tablet zoom, dragging and selection. | [
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] | def mouseReleaseEvent(self, event):
"""
Apply tablet zoom, dragging and selection.
"""
# Zoom the View.
if self.currentState == '.ZOOM_VIEW':
self.offset = 0
self.zoomDirection = 0
self.zoomIncr = 0
self.setInteractive(True)
# Drag View.
elif self.currentState == 'DRAG_VIEW':
self.setCursor(QtCore.Qt.ArrowCursor)
self.setInteractive(True)
# Selection.
elif self.currentState == 'SELECTION':
self.rubberband.setGeometry(QtCore.QRect(self.origin,
event.pos()).normalized())
painterPath = self._releaseRubberband()
self.setInteractive(True)
self.scene().setSelectionArea(painterPath)
# Add Selection.
elif self.currentState == 'ADD_SELECTION':
self.rubberband.setGeometry(QtCore.QRect(self.origin,
event.pos()).normalized())
painterPath = self._releaseRubberband()
self.setInteractive(True)
for item in self.scene().items(painterPath):
item.setSelected(True)
# Subtract Selection.
elif self.currentState == 'SUBTRACT_SELECTION':
self.rubberband.setGeometry(QtCore.QRect(self.origin,
event.pos()).normalized())
painterPath = self._releaseRubberband()
self.setInteractive(True)
for item in self.scene().items(painterPath):
item.setSelected(False)
# Toggle Selection
elif self.currentState == 'TOGGLE_SELECTION':
self.rubberband.setGeometry(QtCore.QRect(self.origin,
event.pos()).normalized())
painterPath = self._releaseRubberband()
self.setInteractive(True)
for item in self.scene().items(painterPath):
if item.isSelected():
item.setSelected(False)
else:
item.setSelected(True)
self.currentState = 'DEFAULT'
super(Nodz, self).mouseReleaseEvent(event) | [
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odlgroup/odl | 0b088df8dc4621c68b9414c3deff9127f4c4f11d | odl/space/npy_tensors.py | python | NumpyTensorSpace.is_weighted | (self) | return not (
isinstance(self.weighting, NumpyTensorSpaceConstWeighting) and
self.weighting.const == 1.0) | Return ``True`` if the space is not weighted by constant 1.0. | Return ``True`` if the space is not weighted by constant 1.0. | [
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"""Return ``True`` if the space is not weighted by constant 1.0."""
return not (
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timkpaine/pyEX | 254acd2b0cf7cb7183100106f4ecc11d1860c46a | pyEX/stats/stats.py | python | dailyDF | (*args, **kwargs) | return _toDatetime(pd.DataFrame(daily(*args, **kwargs))) | [] | def dailyDF(*args, **kwargs):
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aws/sagemaker-containers | 526dda90d636c7fb0c25791e6c57d077bd972000 | src/sagemaker_containers/_env.py | python | TrainingEnv.input_config_dir | (self) | return self._input_config_dir | The directory where standard SageMaker configuration files are located, e.g.
/opt/ml/input/config/.
SageMaker training creates the following files in this folder when training starts:
- `hyperparameters.json`: Amazon SageMaker makes the hyperparameters in a
CreateTrainingJob request available in this file.
- `inputdataconfig.json`: You specify data channel information in the
InputDataConfig parameter in a CreateTrainingJob request.
Amazon SageMaker makes this information available in this
file.
- `resourceconfig.json`: name of the current host and all host containers in the
training More information about this files can be find here:
https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms-training-algo.html
Returns:
str: the path of the input directory, e.g. /opt/ml/input/config/ | The directory where standard SageMaker configuration files are located, e.g.
/opt/ml/input/config/.
SageMaker training creates the following files in this folder when training starts:
- `hyperparameters.json`: Amazon SageMaker makes the hyperparameters in a
CreateTrainingJob request available in this file.
- `inputdataconfig.json`: You specify data channel information in the
InputDataConfig parameter in a CreateTrainingJob request.
Amazon SageMaker makes this information available in this
file.
- `resourceconfig.json`: name of the current host and all host containers in the
training More information about this files can be find here:
https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms-training-algo.html
Returns:
str: the path of the input directory, e.g. /opt/ml/input/config/ | [
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"""The directory where standard SageMaker configuration files are located, e.g.
/opt/ml/input/config/.
SageMaker training creates the following files in this folder when training starts:
- `hyperparameters.json`: Amazon SageMaker makes the hyperparameters in a
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- `inputdataconfig.json`: You specify data channel information in the
InputDataConfig parameter in a CreateTrainingJob request.
Amazon SageMaker makes this information available in this
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training More information about this files can be find here:
https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms-training-algo.html
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] | https://github.com/aws/sagemaker-containers/blob/526dda90d636c7fb0c25791e6c57d077bd972000/src/sagemaker_containers/_env.py#L751-L767 | |
python-telegram-bot/python-telegram-bot | ade1529986f5b6d394a65372d6a27045a70725b2 | examples/nestedconversationbot.py | python | show_data | (update: Update, context: CallbackContext) | return SHOWING | Pretty print gathered data. | Pretty print gathered data. | [
"Pretty",
"print",
"gathered",
"data",
"."
] | def show_data(update: Update, context: CallbackContext) -> str:
"""Pretty print gathered data."""
def prettyprint(user_data: Dict[str, Any], level: str) -> str:
people = user_data.get(level)
if not people:
return '\nNo information yet.'
text = ''
if level == SELF:
for person in user_data[level]:
text += f"\nName: {person.get(NAME, '-')}, Age: {person.get(AGE, '-')}"
else:
male, female = _name_switcher(level)
for person in user_data[level]:
gender = female if person[GENDER] == FEMALE else male
text += f"\n{gender}: Name: {person.get(NAME, '-')}, Age: {person.get(AGE, '-')}"
return text
user_data = context.user_data
text = f"Yourself:{prettyprint(user_data, SELF)}"
text += f"\n\nParents:{prettyprint(user_data, PARENTS)}"
text += f"\n\nChildren:{prettyprint(user_data, CHILDREN)}"
buttons = [[InlineKeyboardButton(text='Back', callback_data=str(END))]]
keyboard = InlineKeyboardMarkup(buttons)
update.callback_query.answer()
update.callback_query.edit_message_text(text=text, reply_markup=keyboard)
user_data[START_OVER] = True
return SHOWING | [
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replit-archive/empythoned | 977ec10ced29a3541a4973dc2b59910805695752 | dist/lib/python2.7/email/message.py | python | Message.get_param | (self, param, failobj=None, header='content-type',
unquote=True) | return failobj | Return the parameter value if found in the Content-Type header.
Optional failobj is the object to return if there is no Content-Type
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param = msg.get_param('foo')
if isinstance(param, tuple):
param = unicode(param[2], param[0] or 'us-ascii')
In any case, the parameter value (either the returned string, or the
VALUE item in the 3-tuple) is always unquoted, unless unquote is set
to False. | Return the parameter value if found in the Content-Type header. | [
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"""Return the parameter value if found in the Content-Type header.
Optional failobj is the object to return if there is no Content-Type
header, or the Content-Type header has no such parameter. Optional
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"""
if header not in self:
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for k, v in self._get_params_preserve(failobj, header):
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if unquote:
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return v
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makerbot/ReplicatorG | d6f2b07785a5a5f1e172fb87cb4303b17c575d5d | skein_engines/skeinforge-35/skeinforge_application/skeinforge_plugins/craft_plugins/temperature.py | python | TemperatureRepository.__init__ | (self) | Set the default settings, execute title & settings fileName. | Set the default settings, execute title & settings fileName. | [
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] | def __init__(self):
"Set the default settings, execute title & settings fileName."
skeinforge_profile.addListsToCraftTypeRepository('skeinforge_application.skeinforge_plugins.craft_plugins.temperature.html', self )
self.fileNameInput = settings.FileNameInput().getFromFileName( fabmetheus_interpret.getGNUTranslatorGcodeFileTypeTuples(), 'Open File for Temperature', self, '')
self.activateTemperature = settings.BooleanSetting().getFromValue('Activate Temperature:', self, True )
settings.LabelSeparator().getFromRepository(self)
settings.LabelDisplay().getFromName('- Rate -', self )
self.coolingRate = settings.FloatSpin().getFromValue( 1.0, 'Cooling Rate (Celcius/second):', self, 20.0, 3.0 )
self.heatingRate = settings.FloatSpin().getFromValue( 1.0, 'Heating Rate (Celcius/second):', self, 20.0, 10.0 )
settings.LabelSeparator().getFromRepository(self)
settings.LabelDisplay().getFromName('- Temperature -', self )
self.baseTemperature = settings.FloatSpin().getFromValue( 140.0, 'Base Temperature (Celcius):', self, 260.0, 200.0 )
self.interfaceTemperature = settings.FloatSpin().getFromValue( 140.0, 'Interface Temperature (Celcius):', self, 260.0, 200.0 )
self.objectFirstLayerInfillTemperature = settings.FloatSpin().getFromValue( 140.0, 'Object First Layer Infill Temperature (Celcius):', self, 260.0, 195.0 )
self.objectFirstLayerPerimeterTemperature = settings.FloatSpin().getFromValue( 140.0, 'Object First Layer Perimeter Temperature (Celcius):', self, 260.0, 220.0 )
self.objectNextLayersTemperature = settings.FloatSpin().getFromValue( 140.0, 'Object Next Layers Temperature (Celcius):', self, 260.0, 230.0 )
self.supportLayersTemperature = settings.FloatSpin().getFromValue( 140.0, 'Support Layers Temperature (Celcius):', self, 260.0, 200.0 )
self.supportedLayersTemperature = settings.FloatSpin().getFromValue( 140.0, 'Supported Layers Temperature (Celcius):', self, 260.0, 230.0 )
self.executeTitle = 'Temperature' | [
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FriedAppleTeam/FRAPL | 89c14d57e0cc77b915fe1e95f60e9e1847699103 | Framework/FridaLink/FridaLink/Core/HookEngine.py | python | HookEngineProtocol.handleHookInstBreakOnce | (self, screenEA = None) | [] | def handleHookInstBreakOnce(self, screenEA = None):
if screenEA is not None:
address = screenEA
else:
address = ScreenEA()
self.handleQuickInstHook(address, True, True) | [
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DataDog/integrations-core | 934674b29d94b70ccc008f76ea172d0cdae05e1e | nginx_ingress_controller/datadog_checks/nginx_ingress_controller/config_models/defaults.py | python | instance_empty_default_hostname | (field, value) | return False | [] | def instance_empty_default_hostname(field, value):
return False | [
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JiYou/openstack | 8607dd488bde0905044b303eb6e52bdea6806923 | chap19/monitor/monitor/monitor/openstack/common/setup.py | python | _get_revno | (git_dir) | return len(revlist.splitlines()) | Return the number of commits since the most recent tag.
We use git-describe to find this out, but if there are no
tags then we fall back to counting commits since the beginning
of time. | Return the number of commits since the most recent tag. | [
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] | def _get_revno(git_dir):
"""Return the number of commits since the most recent tag.
We use git-describe to find this out, but if there are no
tags then we fall back to counting commits since the beginning
of time.
"""
describe = _run_shell_command(
"git --git-dir=%s describe --always" % git_dir)
if "-" in describe:
return describe.rsplit("-", 2)[-2]
# no tags found
revlist = _run_shell_command(
"git --git-dir=%s rev-list --abbrev-commit HEAD" % git_dir)
return len(revlist.splitlines()) | [
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4shadoww/hakkuframework | 409a11fc3819d251f86faa3473439f8c19066a21 | lib/scapy/arch/linux.py | python | VEthPair.up | (self) | set veth pair links up
:raises subprocess.CalledProcessError if operation fails | set veth pair links up
:raises subprocess.CalledProcessError if operation fails | [
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] | def up(self):
# type: () -> None
"""
set veth pair links up
:raises subprocess.CalledProcessError if operation fails
"""
for idx in [0, 1]:
subprocess.check_call(["ip", "link", "set", self.ifaces[idx], "up"]) | [
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nschloe/quadpy | c4c076d8ddfa968486a2443a95e2fb3780dcde0f | src/quadpy/t2/_albrecht_collatz.py | python | albrecht_collatz | () | return T2Scheme("Albrecht-Collatz", d, 3, source, tol=2.776e-16) | [] | def albrecht_collatz():
d = {"d3_aa": [[frac(1, 30), frac(9, 30)], [frac(1, 2), frac(1, 6)]]}
return T2Scheme("Albrecht-Collatz", d, 3, source, tol=2.776e-16) | [
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PyCQA/astroid | a815443f62faae05249621a396dcf0afd884a619 | astroid/nodes/node_classes.py | python | If.block_range | (self, lineno) | return self._elsed_block_range(lineno, self.orelse, self.body[0].fromlineno - 1) | Get a range from the given line number to where this node ends.
:param lineno: The line number to start the range at.
:type lineno: int
:returns: The range of line numbers that this node belongs to,
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"""Get a range from the given line number to where this node ends.
:param lineno: The line number to start the range at.
:type lineno: int
:returns: The range of line numbers that this node belongs to,
starting at the given line number.
:rtype: tuple(int, int)
"""
if lineno == self.body[0].fromlineno:
return lineno, lineno
if lineno <= self.body[-1].tolineno:
return lineno, self.body[-1].tolineno
return self._elsed_block_range(lineno, self.orelse, self.body[0].fromlineno - 1) | [
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beeware/toga | 090370a943bdeefcdbe035b1621fbc7caeebdf1a | src/cocoa/toga_cocoa/widgets/canvas.py | python | Canvas.set_on_resize | (self, handler) | No special handling required. | No special handling required. | [
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openshift/openshift-tools | 1188778e728a6e4781acf728123e5b356380fe6f | openshift/installer/vendored/openshift-ansible-3.9.14-1/roles/openshift_facts/library/openshift_facts.py | python | set_url_facts_if_unset | (facts) | return facts | Set url facts if not already present in facts dict
Args:
facts (dict): existing facts
Returns:
dict: the facts dict updated with the generated url facts if they
were not already present | Set url facts if not already present in facts dict | [
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] | def set_url_facts_if_unset(facts):
""" Set url facts if not already present in facts dict
Args:
facts (dict): existing facts
Returns:
dict: the facts dict updated with the generated url facts if they
were not already present
"""
if 'master' in facts:
hostname = facts['common']['hostname']
cluster_hostname = facts['master'].get('cluster_hostname')
cluster_public_hostname = facts['master'].get('cluster_public_hostname')
public_hostname = facts['common']['public_hostname']
api_hostname = cluster_hostname if cluster_hostname else hostname
api_public_hostname = cluster_public_hostname if cluster_public_hostname else public_hostname
console_path = facts['master']['console_path']
etcd_hosts = facts['master']['etcd_hosts']
use_ssl = dict(
api=facts['master']['api_use_ssl'],
public_api=facts['master']['api_use_ssl'],
loopback_api=facts['master']['api_use_ssl'],
console=facts['master']['console_use_ssl'],
public_console=facts['master']['console_use_ssl'],
etcd=facts['master']['etcd_use_ssl']
)
ports = dict(
api=facts['master']['api_port'],
public_api=facts['master']['api_port'],
loopback_api=facts['master']['api_port'],
console=facts['master']['console_port'],
public_console=facts['master']['console_port'],
etcd=facts['master']['etcd_port'],
)
etcd_urls = []
if etcd_hosts != '':
facts['master']['etcd_port'] = ports['etcd']
for host in etcd_hosts:
etcd_urls.append(format_url(use_ssl['etcd'], host,
ports['etcd']))
else:
etcd_urls = [format_url(use_ssl['etcd'], hostname,
ports['etcd'])]
facts['master'].setdefault('etcd_urls', etcd_urls)
prefix_hosts = [('api', api_hostname),
('public_api', api_public_hostname),
('loopback_api', hostname)]
for prefix, host in prefix_hosts:
facts['master'].setdefault(prefix + '_url', format_url(use_ssl[prefix],
host,
ports[prefix]))
r_lhn = "{0}:{1}".format(hostname, ports['api']).replace('.', '-')
r_lhu = "system:openshift-master/{0}:{1}".format(api_hostname, ports['api']).replace('.', '-')
facts['master'].setdefault('loopback_cluster_name', r_lhn)
facts['master'].setdefault('loopback_context_name', "default/{0}/system:openshift-master".format(r_lhn))
facts['master'].setdefault('loopback_user', r_lhu)
prefix_hosts = [('console', api_hostname), ('public_console', api_public_hostname)]
for prefix, host in prefix_hosts:
facts['master'].setdefault(prefix + '_url', format_url(use_ssl[prefix],
host,
ports[prefix],
console_path))
return facts | [
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zapier/email-reply-parser | f67a872de3c7bebe3bd836afec60ab3f1201e8a6 | email_reply_parser/__init__.py | python | EmailMessage.reply | (self) | return '\n'.join(reply) | Captures reply message within email | Captures reply message within email | [
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""" Captures reply message within email
"""
reply = []
for f in self.fragments:
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reply.append(f.content)
return '\n'.join(reply) | [
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Chia-Network/chia-blockchain | 34d44c1324ae634a0896f7b02eaa2802af9526cd | chia/farmer/farmer_api.py | python | FarmerAPI.new_proof_of_space | (
self, new_proof_of_space: harvester_protocol.NewProofOfSpace, peer: ws.WSChiaConnection
) | This is a response from the harvester, for a NewChallenge. Here we check if the proof
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self, new_proof_of_space: harvester_protocol.NewProofOfSpace, peer: ws.WSChiaConnection
):
"""
This is a response from the harvester, for a NewChallenge. Here we check if the proof
of space is sufficiently good, and if so, we ask for the whole proof.
"""
if new_proof_of_space.sp_hash not in self.farmer.number_of_responses:
self.farmer.number_of_responses[new_proof_of_space.sp_hash] = 0
self.farmer.cache_add_time[new_proof_of_space.sp_hash] = uint64(int(time.time()))
max_pos_per_sp = 5
if self.farmer.constants.NETWORK_TYPE != NetworkType.MAINNET:
# This is meant to make testnets more stable, when difficulty is very low
if self.farmer.number_of_responses[new_proof_of_space.sp_hash] > max_pos_per_sp:
self.farmer.log.info(
f"Surpassed {max_pos_per_sp} PoSpace for one SP, no longer submitting PoSpace for signage point "
f"{new_proof_of_space.sp_hash}"
)
return None
if new_proof_of_space.sp_hash not in self.farmer.sps:
self.farmer.log.warning(
f"Received response for a signage point that we do not have {new_proof_of_space.sp_hash}"
)
return None
sps = self.farmer.sps[new_proof_of_space.sp_hash]
for sp in sps:
computed_quality_string = new_proof_of_space.proof.verify_and_get_quality_string(
self.farmer.constants,
new_proof_of_space.challenge_hash,
new_proof_of_space.sp_hash,
)
if computed_quality_string is None:
self.farmer.log.error(f"Invalid proof of space {new_proof_of_space.proof}")
return None
self.farmer.number_of_responses[new_proof_of_space.sp_hash] += 1
required_iters: uint64 = calculate_iterations_quality(
self.farmer.constants.DIFFICULTY_CONSTANT_FACTOR,
computed_quality_string,
new_proof_of_space.proof.size,
sp.difficulty,
new_proof_of_space.sp_hash,
)
# If the iters are good enough to make a block, proceed with the block making flow
if required_iters < calculate_sp_interval_iters(self.farmer.constants, sp.sub_slot_iters):
# Proceed at getting the signatures for this PoSpace
request = harvester_protocol.RequestSignatures(
new_proof_of_space.plot_identifier,
new_proof_of_space.challenge_hash,
new_proof_of_space.sp_hash,
[sp.challenge_chain_sp, sp.reward_chain_sp],
)
if new_proof_of_space.sp_hash not in self.farmer.proofs_of_space:
self.farmer.proofs_of_space[new_proof_of_space.sp_hash] = []
self.farmer.proofs_of_space[new_proof_of_space.sp_hash].append(
(
new_proof_of_space.plot_identifier,
new_proof_of_space.proof,
)
)
self.farmer.cache_add_time[new_proof_of_space.sp_hash] = uint64(int(time.time()))
self.farmer.quality_str_to_identifiers[computed_quality_string] = (
new_proof_of_space.plot_identifier,
new_proof_of_space.challenge_hash,
new_proof_of_space.sp_hash,
peer.peer_node_id,
)
self.farmer.cache_add_time[computed_quality_string] = uint64(int(time.time()))
await peer.send_message(make_msg(ProtocolMessageTypes.request_signatures, request))
p2_singleton_puzzle_hash = new_proof_of_space.proof.pool_contract_puzzle_hash
if p2_singleton_puzzle_hash is not None:
# Otherwise, send the proof of space to the pool
# When we win a block, we also send the partial to the pool
if p2_singleton_puzzle_hash not in self.farmer.pool_state:
self.farmer.log.info(f"Did not find pool info for {p2_singleton_puzzle_hash}")
return
pool_state_dict: Dict = self.farmer.pool_state[p2_singleton_puzzle_hash]
pool_url = pool_state_dict["pool_config"].pool_url
if pool_url == "":
return
if pool_state_dict["current_difficulty"] is None:
self.farmer.log.warning(
f"No pool specific difficulty has been set for {p2_singleton_puzzle_hash}, "
f"check communication with the pool, skipping this partial to {pool_url}."
)
return
required_iters = calculate_iterations_quality(
self.farmer.constants.DIFFICULTY_CONSTANT_FACTOR,
computed_quality_string,
new_proof_of_space.proof.size,
pool_state_dict["current_difficulty"],
new_proof_of_space.sp_hash,
)
if required_iters >= calculate_sp_interval_iters(
self.farmer.constants, self.farmer.constants.POOL_SUB_SLOT_ITERS
):
self.farmer.log.info(
f"Proof of space not good enough for pool {pool_url}: {pool_state_dict['current_difficulty']}"
)
return
authentication_token_timeout = pool_state_dict["authentication_token_timeout"]
if authentication_token_timeout is None:
self.farmer.log.warning(
f"No pool specific authentication_token_timeout has been set for {p2_singleton_puzzle_hash}"
f", check communication with the pool."
)
return
# Submit partial to pool
is_eos = new_proof_of_space.signage_point_index == 0
payload = PostPartialPayload(
pool_state_dict["pool_config"].launcher_id,
get_current_authentication_token(authentication_token_timeout),
new_proof_of_space.proof,
new_proof_of_space.sp_hash,
is_eos,
peer.peer_node_id,
)
# The plot key is 2/2 so we need the harvester's half of the signature
m_to_sign = payload.get_hash()
request = harvester_protocol.RequestSignatures(
new_proof_of_space.plot_identifier,
new_proof_of_space.challenge_hash,
new_proof_of_space.sp_hash,
[m_to_sign],
)
response: Any = await peer.request_signatures(request)
if not isinstance(response, harvester_protocol.RespondSignatures):
self.farmer.log.error(f"Invalid response from harvester: {response}")
return
assert len(response.message_signatures) == 1
plot_signature: Optional[G2Element] = None
for sk in self.farmer.get_private_keys():
pk = sk.get_g1()
if pk == response.farmer_pk:
agg_pk = ProofOfSpace.generate_plot_public_key(response.local_pk, pk, True)
assert agg_pk == new_proof_of_space.proof.plot_public_key
sig_farmer = AugSchemeMPL.sign(sk, m_to_sign, agg_pk)
taproot_sk: PrivateKey = ProofOfSpace.generate_taproot_sk(response.local_pk, pk)
taproot_sig: G2Element = AugSchemeMPL.sign(taproot_sk, m_to_sign, agg_pk)
plot_signature = AugSchemeMPL.aggregate(
[sig_farmer, response.message_signatures[0][1], taproot_sig]
)
assert AugSchemeMPL.verify(agg_pk, m_to_sign, plot_signature)
authentication_pk = pool_state_dict["pool_config"].authentication_public_key
if bytes(authentication_pk) is None:
self.farmer.log.error(f"No authentication sk for {authentication_pk}")
return
authentication_sk: PrivateKey = self.farmer.authentication_keys[bytes(authentication_pk)]
authentication_signature = AugSchemeMPL.sign(authentication_sk, m_to_sign)
assert plot_signature is not None
agg_sig: G2Element = AugSchemeMPL.aggregate([plot_signature, authentication_signature])
post_partial_request: PostPartialRequest = PostPartialRequest(payload, agg_sig)
self.farmer.log.info(
f"Submitting partial for {post_partial_request.payload.launcher_id.hex()} to {pool_url}"
)
pool_state_dict["points_found_since_start"] += pool_state_dict["current_difficulty"]
pool_state_dict["points_found_24h"].append((time.time(), pool_state_dict["current_difficulty"]))
try:
async with aiohttp.ClientSession() as session:
async with session.post(
f"{pool_url}/partial",
json=post_partial_request.to_json_dict(),
ssl=ssl_context_for_root(get_mozilla_ca_crt(), log=self.farmer.log),
headers={"User-Agent": f"Chia Blockchain v.{__version__}"},
) as resp:
if resp.ok:
pool_response: Dict = json.loads(await resp.text())
self.farmer.log.info(f"Pool response: {pool_response}")
if "error_code" in pool_response:
self.farmer.log.error(
f"Error in pooling: "
f"{pool_response['error_code'], pool_response['error_message']}"
)
pool_state_dict["pool_errors_24h"].append(pool_response)
if pool_response["error_code"] == PoolErrorCode.PROOF_NOT_GOOD_ENOUGH.value:
self.farmer.log.error(
"Partial not good enough, forcing pool farmer update to "
"get our current difficulty."
)
pool_state_dict["next_farmer_update"] = 0
await self.farmer.update_pool_state()
else:
new_difficulty = pool_response["new_difficulty"]
pool_state_dict["points_acknowledged_since_start"] += new_difficulty
pool_state_dict["points_acknowledged_24h"].append((time.time(), new_difficulty))
pool_state_dict["current_difficulty"] = new_difficulty
else:
self.farmer.log.error(f"Error sending partial to {pool_url}, {resp.status}")
except Exception as e:
self.farmer.log.error(f"Error connecting to pool: {e}")
return
return | [
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linxid/Machine_Learning_Study_Path | 558e82d13237114bbb8152483977806fc0c222af | Machine Learning In Action/Chapter8-Regression/venv/Lib/site-packages/pip-9.0.1-py3.6.egg/pip/_vendor/html5lib/treebuilders/base.py | python | TreeBuilder.generateImpliedEndTags | (self, exclude=None) | [] | def generateImpliedEndTags(self, exclude=None):
name = self.openElements[-1].name
# XXX td, th and tr are not actually needed
if (name in frozenset(("dd", "dt", "li", "option", "optgroup", "p", "rp", "rt")) and
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# XXX This is not entirely what the specification says. We should
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home-assistant/core | 265ebd17a3f17ed8dc1e9bdede03ac8e323f1ab1 | homeassistant/helpers/entity.py | python | Entity.icon | (self) | return None | Return the icon to use in the frontend, if any. | Return the icon to use in the frontend, if any. | [
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"""Return the icon to use in the frontend, if any."""
if hasattr(self, "_attr_icon"):
return self._attr_icon
if hasattr(self, "entity_description"):
return self.entity_description.icon
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IntelPython/sdc | 1ebf55c00ef38dfbd401a70b3945e352a5a38b87 | examples/series/series_groupby.py | python | series_groupby | () | return S.groupby(by).mean() | [] | def series_groupby():
S = pd.Series([390., 350., 30., 20.])
by = np.asarray([0, 1, 0, 1])
# Expect Series of pd.Series([210.0, 185.0], index=[0, 1])
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robhagemans/pcbasic | c3a043b46af66623a801e18a38175be077251ada | pcbasic/basic/converter/lister.py | python | Lister.token_to_line_number | (self, trail) | return struct.unpack_from('<H', trail, 2)[0] | Unpack a line number token trail, -1 if end of program. | Unpack a line number token trail, -1 if end of program. | [
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google/capirca | 679e3885e3a5e5e129dc2dfab204ec44d63b26a4 | capirca/lib/aclgenerator.py | python | ACLGenerator._GetSupportedTokens | (self) | return supported_tokens, supported_sub_tokens | Build our supported tokens and sub tokens.
Returns:
tuple containing the supported tokens and sub tokens.
Raises:
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] | def _GetSupportedTokens(self):
"""Build our supported tokens and sub tokens.
Returns:
tuple containing the supported tokens and sub tokens.
Raises:
UnsupportedFilterError: Raised when token is not supported.
"""
supported_tokens, supported_sub_tokens = self._BuildTokens()
# make sure we don't have subtokens that are not listed. This should not
# occur unless a platform's tokens/subtokens are changed.
undefined_st = set(supported_sub_tokens) - supported_tokens
if undefined_st:
raise UnsupportedFilterError(
'Found undefined sub tokens missing from the supported token list! '
'These must match. (%s)' % ' '.join(undefined_st))
# all good.
return supported_tokens, supported_sub_tokens | [
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huggingface/transformers | 623b4f7c63f60cce917677ee704d6c93ee960b4b | src/transformers/models/blenderbot/modeling_blenderbot.py | python | BlenderbotPreTrainedModel._set_gradient_checkpointing | (self, module, value=False) | [] | def _set_gradient_checkpointing(self, module, value=False):
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minerllabs/minerl | 0123527c334c96ebb3f0cf313df1552fa4302691 | minerl/herobraine/hero/handlers/translation.py | python | KeymapTranslationHandler.to_hero | (self, x) | What does it mean to do a keymap translation here?
Since hero sends things as commands perhaps we could generalize
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Since hero sends things as commands perhaps we could generalize
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pventuzelo/octopus | e8b8c5a9d5f6d9c63605afe9ef1528ab481ec983 | octopus/engine/disassembler.py | python | Disassembler.disassemble | (self, bytecode=None, offset=0, r_format='list') | Generic method to disassemble bytecode
:param bytecode: bytecode sequence
:param offset: start offset
:param r_format: output format ('list'/'text'/'reverse')
:type bytecode: bytes, str
:type offset: int
:type r_format: list, str, dict
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"""Generic method to disassemble bytecode
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:param offset: start offset
:param r_format: output format ('list'/'text'/'reverse')
:type bytecode: bytes, str
:type offset: int
:type r_format: list, str, dict
:return: dissassembly result depending of r_format
:rtype: list, str, dict
"""
# reinitialize class variable
self.attributes_reset()
self.bytecode = bytecode if bytecode else self.bytecode
if not self.bytecode:
raise BytecodeEmptyException()
self.bytecode = bytecode_to_bytes(self.bytecode)
while offset < len(self.bytecode):
instr = self.disassemble_opcode(self.bytecode[offset:], offset)
offset += instr.size
self.instructions.append(instr)
# fill reverse instructions
self.reverse_instructions = {k: v for k, v in
enumerate(self.instructions)}
# return instructions
if r_format == 'list':
return self.instructions
elif r_format == 'text':
return '\n'.join(map(str, self.instructions))
elif r_format == 'reverse':
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GoogleCloudPlatform/PerfKitBenchmarker | 6e3412d7d5e414b8ca30ed5eaf970cef1d919a67 | perfkitbenchmarker/benchmark_spec.py | python | BenchmarkSpec.ConstructNfsService | (self) | Construct the NFS service object.
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"""Construct the NFS service object.
Creates an NFS Service only if an NFS disk is found in the disk_specs.
"""
if self.nfs_service:
logging.info('NFS service already created: %s', self.nfs_service)
return
for group_spec in self.vms_to_boot.values():
if not group_spec.disk_spec or not group_spec.vm_count:
continue
disk_spec = group_spec.disk_spec
if disk_spec.disk_type != disk.NFS:
continue
# Choose which nfs_service to create.
if disk_spec.nfs_ip_address:
self.nfs_service = nfs_service.StaticNfsService(disk_spec)
elif disk_spec.nfs_managed:
cloud = group_spec.cloud
providers.LoadProvider(cloud)
nfs_class = nfs_service.GetNfsServiceClass(cloud)
self.nfs_service = nfs_class(disk_spec, group_spec.vm_spec.zone)
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self.nfs_service = nfs_service.UnmanagedNfsService(disk_spec,
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Pyomo/pyomo | dbd4faee151084f343b893cc2b0c04cf2b76fd92 | pyomo/contrib/pynumero/sparse/block_matrix.py | python | BlockMatrix.copy_structure | (self) | return result | Makes a copy of the structure of this BlockMatrix. This proivides a
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the same number of nonzeros.
Returns
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m, n = self.bshape
result = BlockMatrix(m, n)
for row in range(m):
if self.is_row_size_defined(row):
result.set_row_size(row, self.get_row_size(row))
for col in range(n):
if self.is_col_size_defined(col):
result.set_col_size(col, self.get_col_size(col))
ii, jj = np.nonzero(self._block_mask)
for i, j in zip(ii, jj):
if isinstance(self._blocks[i, j], BlockMatrix):
result.set_block(i, j, self._blocks[i, j].copy_structure())
else:
nrows, ncols = self._blocks[i, j].shape
result.set_block(i, j, coo_matrix((nrows, ncols)))
return result | [
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wxWidgets/Phoenix | b2199e299a6ca6d866aa6f3d0888499136ead9d6 | wx/lib/ogl/basic.py | python | Shape.HitTest | (self, x, y) | return False | Given a point on a canvas, returns `True` if the point was on the
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:param `x`: the x position
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if abs(height) < 4:
height = 4.0
width += 4 # Allowance for inaccurate mousing
height += 4
left = self._xpos - width / 2.0
top = self._ypos - height / 2.0
right = self._xpos + width / 2.0
bottom = self._ypos + height / 2.0
nearest_attachment = 0
# If within the bounding box, check the attachment points
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if x >= left and x <= right and y >= top and y <= bottom:
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nearest = 999999
# GetAttachmentPosition[Edge] takes a logical attachment position,
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for i in range(n):
e = self.GetAttachmentPositionEdge(i)
if e:
xp, yp = e
l = math.sqrt(((xp - x) * (xp - x)) + (yp - y) * (yp - y))
if l < nearest:
nearest = l
nearest_attachment = i
return nearest_attachment, nearest
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cloudera/hue | 23f02102d4547c17c32bd5ea0eb24e9eadd657a4 | desktop/core/ext-py/boto-2.46.1/boto/opsworks/layer1.py | python | OpsWorksConnection.stop_stack | (self, stack_id) | return self.make_request(action='StopStack',
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Stops a specified stack.
**Required Permissions**: To use this action, an IAM user must
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policy that explicitly grants permissions. For more
information on user permissions, see `Managing User
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:type stack_id: string
:param stack_id: The stack ID.
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params = {'StackId': stack_id, }
return self.make_request(action='StopStack',
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feliam/pysymemu | ad02e52122099d537372eb4d11fd5024b8a3857f | cpu.py | python | Cpu.DEC | (cpu, dest) | Decrements by 1.
Subtracts 1 from the destination operand, while preserving the state of the CF flag. The destination
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The OF, SF, ZF, AF, and PF flags are set according to the result::
DEST = DEST - 1;
@param cpu: current CPU.
@param dest: destination operand. | Decrements by 1.
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without disturbing the CF flag. (To perform a decrement operation that updates the CF flag, use a SUB
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'''
Decrements by 1.
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arg0 = dest.read()
res = dest.write(arg0-1)
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interpretml/interpret-text | d74efc985270aaa2b3ab779408597d9505e9ea1d | python/interpret_text/experimental/introspective_rationale/explainer.py | python | IntrospectiveRationaleExplainer.train | (self, *args, **kwargs) | return self.fit(*args, **kwargs) | Optionally pretrain the generator's introspective classifier, then
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""" Optionally pretrain the generator's introspective classifier, then
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JacquesLucke/animation_nodes | b1e3ace8dcb0a771fd882fc3ac4e490b009fa0d1 | animation_nodes/node_link_conversion.py | python | ConvertNormalToEuler.insert | (self, nodeTree, origin, target, dataOrigin) | [] | def insert(self, nodeTree, origin, target, dataOrigin):
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holzschu/Carnets | 44effb10ddfc6aa5c8b0687582a724ba82c6b547 | Library/lib/python3.7/site-packages/tornado-6.0.1-py3.7-macosx-12.1-iPad6,7.egg/tornado/web.py | python | RequestHandler.xsrf_form_html | (self) | return (
'<input type="hidden" name="_xsrf" value="'
+ escape.xhtml_escape(self.xsrf_token)
+ '"/>'
) | An HTML ``<input/>`` element to be included with all POST forms.
It defines the ``_xsrf`` input value, which we check on all POST
requests to prevent cross-site request forgery. If you have set
the ``xsrf_cookies`` application setting, you must include this
HTML within all of your HTML forms.
In a template, this method should be called with ``{% module
xsrf_form_html() %}``
See `check_xsrf_cookie()` above for more information. | An HTML ``<input/>`` element to be included with all POST forms. | [
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"""An HTML ``<input/>`` element to be included with all POST forms.
It defines the ``_xsrf`` input value, which we check on all POST
requests to prevent cross-site request forgery. If you have set
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In a template, this method should be called with ``{% module
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See `check_xsrf_cookie()` above for more information.
"""
return (
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Ridter/MyJSRat | 1be0b812eff4898618fb4cb4f678efdb360d7368 | MyJSRat.py | python | myHandler.log_message | (self, format, *args) | return | Custom Log Handler to Spit out on to stderr | Custom Log Handler to Spit out on to stderr | [
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Anorov/PySocks | c2fa43cbe1091e799e248e8e4433978916791a8b | socks.py | python | socksocket.get_proxy_sockname | (self) | return self.proxy_sockname | Returns the bound IP address and port number at the proxy. | Returns the bound IP address and port number at the proxy. | [
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quantmind/pulsar | fee44e871954aa6ca36d00bb5a3739abfdb89b26 | pulsar/apps/wsgi/wrappers.py | python | WsgiRequest.absolute_uri | (self, location=None, scheme=None, **query) | Builds an absolute URI from ``location`` and variables
available in this request.
If no ``location`` is specified, the relative URI is built from
:meth:`full_path`. | Builds an absolute URI from ``location`` and variables
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If no ``location`` is specified, the relative URI is built from
:meth:`full_path`.
"""
if not is_absolute_uri(location):
if location or location is None:
location = self.full_path(location, **query)
if not scheme:
scheme = self.is_secure and 'https' or 'http'
base = '%s://%s' % (scheme, self.get_host())
return '%s%s' % (base, location)
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return iri_to_uri(location)
else:
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StanfordVL/taskonomy | 9f814867b5fe4165860862211e8e99b0f200144d | taskbank/lib/data/load_ops.py | python | rescale_image | (im, new_scale=[-1.,1.], current_scale=None, no_clip=False) | return im | Rescales an image pixel values to target_scale
Args:
img: A np.float_32 array, assumed between [0,1]
new_scale: [min,max]
current_scale: If not supplied, it is assumed to be in:
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[0, 2^16]: if dtype=uint
[0, 255]: if dtype=ubyte
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img: A np.float_32 array, assumed between [0,1]
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QUANTAXIS/QUANTAXIS | d6eccb97c8385854aa596d6ba8d70ec0655519ff | QUANTAXIS/QAFetch/QAbinance.py | python | QA_fetch_binance_kline_min | (
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start_time,
end_time,
frequency,
callback_func=None
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时间倒序切片获取算法，是各大交易所获取1min数据的神器，因为大部分交易所直接请求跨月跨年的1min分钟数据
会直接返回空值，只有将 start_epoch，end_epoch 切片细分到 200/300 bar 以内，才能正确返回 kline，
火币和binance，OKEx 均为如此，用上面那个函数的方式去直接请求上万bar 的分钟 kline 数据是不会有结果的。 | Get the latest symbol‘s candlestick data with time slices
时间倒序切片获取算法，是各大交易所获取1min数据的神器，因为大部分交易所直接请求跨月跨年的1min分钟数据
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symbol,
start_time,
end_time,
frequency,
callback_func=None
):
"""
Get the latest symbol‘s candlestick data with time slices
时间倒序切片获取算法，是各大交易所获取1min数据的神器，因为大部分交易所直接请求跨月跨年的1min分钟数据
会直接返回空值，只有将 start_epoch，end_epoch 切片细分到 200/300 bar 以内，才能正确返回 kline，
火币和binance，OKEx 均为如此，用上面那个函数的方式去直接请求上万bar 的分钟 kline 数据是不会有结果的。
"""
reqParams = {}
reqParams['from'] = end_time - FREQUENCY_SHIFTING[frequency]
reqParams['to'] = end_time
requested_counter = 1
datas = list()
while (reqParams['to'] > start_time):
if ((reqParams['from'] > QA_util_datetime_to_Unix_timestamp())) or \
((reqParams['from'] > reqParams['to'])):
# 出现“未来”时间，一般是默认时区设置，或者时间窗口滚动前移错误造成的
QA_util_log_info(
'A unexpected \'Future\' timestamp got, Please check self.missing_data_list_func param \'tzlocalize\' set. More info: {:s}@{:s} at {:s} but current time is {}'
.format(
symbol,
frequency,
QA_util_print_timestamp(reqParams['from']),
QA_util_print_timestamp(
QA_util_datetime_to_Unix_timestamp()
)
)
)
# 跳到下一个时间段
reqParams['to'] = int(reqParams['from'] - 1)
reqParams['from'] = int(reqParams['from'] - FREQUENCY_SHIFTING[frequency])
continue
klines = QA_fetch_binance_kline_with_auto_retry(
symbol,
reqParams['from'],
reqParams['to'],
frequency,
)
if (klines is None) or \
(len(klines) == 0) or \
('error' in klines):
# 出错放弃
break
reqParams['to'] = int(reqParams['from'] - 1)
reqParams['from'] = int(reqParams['from'] - FREQUENCY_SHIFTING[frequency])
if (callback_func is not None):
frame = format_binance_data_fields(klines, symbol, frequency)
callback_func(frame, Binance2QA_FREQUENCY_DICT[frequency])
if (len(klines) == 0):
return None | [
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NervanaSystems/neon | 8c3fb8a93b4a89303467b25817c60536542d08bd | neon/data/ticker.py | python | Task.fill_buffers | (self, time_steps, inputs, outputs, in_tensor, out_tensor, mask) | Prepare data for delivery to device.
Arguments:
time_steps (int): Number of time steps in this minibatch.
inputs (numpy array): Inputs numpy array
outputs (numpy array): Outputs numpy array
in_tensor (Tensor): Device buffer holding inputs
out_tensor (Tensor): Device buffer holding outputs
mask (numpy array): Device buffer for the output mask | Prepare data for delivery to device. | [
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"""
Prepare data for delivery to device.
Arguments:
time_steps (int): Number of time steps in this minibatch.
inputs (numpy array): Inputs numpy array
outputs (numpy array): Outputs numpy array
in_tensor (Tensor): Device buffer holding inputs
out_tensor (Tensor): Device buffer holding outputs
mask (numpy array): Device buffer for the output mask
"""
# Put inputs and outputs, which are too small, into properly shaped arrays
columns = time_steps * self.be.bsz
inC = np.zeros((self.nin, self.max_columns))
outC = np.zeros((self.nout, self.max_columns))
inC[:, :columns] = inputs
outC[:, :columns] = outputs
# Copy those arrays to device
in_tensor.set(inC)
out_tensor.set(outC)
# Set a mask over the unused part of the buffer
mask[:, :columns] = 1
mask[:, columns:] = 0 | [
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anyoptimization/pymoo | c6426a721d95c932ae6dbb610e09b6c1b0e13594 | pymoo/algorithms/soo/nonconvex/cmaes.py | python | CMAES.__init__ | (self,
x0=None,
sigma=0.1,
normalize=True,
parallelize=True,
maxfevals=np.inf,
tolfun=1e-11,
tolx=1e-11,
restarts=0,
restart_from_best='False',
incpopsize=2,
eval_initial_x=False,
noise_handler=None,
noise_change_sigma_exponent=1,
noise_kappa_exponent=0,
bipop=False,
cmaes_verbose=-9,
verb_log=0,
display=CMAESDisplay(),
**kwargs
) | Parameters
----------
x0 : list or `numpy.ndarray`
initial guess of minimum solution
before the application of the geno-phenotype transformation
according to the ``transformation`` option. It can also be
a string holding a Python expression that is evaluated
to yield the initial guess - this is important in case
restarts are performed so that they start from different
places. Otherwise ``x0`` can also be a `cma.CMAEvolutionStrategy`
object instance, in that case ``sigma0`` can be ``None``.
sigma : float
Initial standard deviation in each coordinate.
``sigma0`` should be about 1/4th of the search domain width
(where the optimum is to be expected). The variables in
``objective_function`` should be scaled such that they
presumably have similar sensitivity.
See also `ScaleCoordinates`.
parallelize : bool
Whether the objective function should be called for each single evaluation or batch wise.
restarts : int, default 0
Number of restarts with increasing population size, see also
parameter ``incpopsize``, implementing the IPOP-CMA-ES restart
strategy, see also parameter ``bipop``; to restart from
different points (recommended), pass ``x0`` as a string.
restart_from_best : bool, default false
Which point to restart from
incpopsize : int
Multiplier for increasing the population size ``popsize`` before each restart
eval_initial_x : bool
Evaluate initial solution, for ``None`` only with elitist option
noise_handler : class
A ``NoiseHandler`` class or instance or ``None``. Example:
``cma.fmin(f, 6 * [1], 1, noise_handler=cma.NoiseHandler(6))``
see ``help(cma.NoiseHandler)``.
noise_change_sigma_exponent : int
Exponent for the sigma increment provided by the noise handler for
additional noise treatment. 0 means no sigma change.
noise_kappa_exponent : int
Instead of applying reevaluations, the "number of evaluations"
is (ab)used as scaling factor kappa (experimental).
bipop : bool
If `True`, run as BIPOP-CMA-ES; BIPOP is a special restart
strategy switching between two population sizings - small
(like the default CMA, but with more focused search) and
large (progressively increased as in IPOP). This makes the
algorithm perform well both on functions with many regularly
or irregularly arranged local optima (the latter by frequently
restarting with small populations). For the `bipop` parameter
to actually take effect, also select non-zero number of
(IPOP) restarts; the recommended setting is ``restarts<=9``
and `x0` passed as a string using `numpy.rand` to generate
initial solutions. Note that small-population restarts
do not count into the total restart count.
AdaptSigma : True
Or False or any CMAAdaptSigmaBase class e.g. CMAAdaptSigmaTPA, CMAAdaptSigmaCSA
CMA_active : True
Negative update, conducted after the original update
CMA_activefac : 1
Learning rate multiplier for active update
CMA_cmean : 1
Learning rate for the mean value
CMA_const_trace : False
Normalize trace, 1, True, "arithm", "geom", "aeig", "geig" are valid
CMA_diagonal : 0*100*N/popsize**0.5
Number of iterations with diagonal covariance matrix, True for always
CMA_eigenmethod : np.linalg.eigh or cma.utilities.math.eig or pygsl.eigen.eigenvectors
CMA_elitist : False or "initial" or True
Elitism likely impairs global search performance
CMA_injections_threshold_keep_len : 0
Keep length if Mahalanobis length is below the given relative threshold
CMA_mirrors : popsize < 6
Values <0.5 are interpreted as fraction, values >1 as numbers (rounded), otherwise about 0.16 is used
CMA_mirrormethod : int, default 2, 0=unconditional, 1=selective, 2=selective with delay
CMA_mu : None
Parents selection parameter, default is popsize // 2
CMA_on : 1
Multiplier for all covariance matrix updates
CMA_sampler : None
A class or instance that implements the interface of
`cma.interfaces.StatisticalModelSamplerWithZeroMeanBaseClass`
CMA_sampler_options : dict
Options passed to `CMA_sampler` class init as keyword arguments
CMA_rankmu : 1.0
Multiplier for rank-mu update learning rate of covariance matrix
CMA_rankone : 1.0
Multiplier for rank-one update learning rate of covariance matrix
CMA_recombination_weights : None
A list, see class RecombinationWeights, overwrites CMA_mu and popsize options
CMA_dampsvec_fac : np.Inf
Tentative and subject to changes, 0.5 would be a "default" damping for sigma vector update
CMA_dampsvec_fade : 0.1
Tentative fading out parameter for sigma vector update
CMA_teststds : None
Factors for non-isotropic initial distr. of C, mainly for test purpose, see CMA_stds for production
CMA_stds : None
Multipliers for sigma0 in each coordinate, not represented in C,
makes scaling_of_variables obsolete
CSA_dampfac : 1
Positive multiplier for step-size damping, 0.3 is close to optimal on the sphere
CSA_damp_mueff_exponent : 0.5
Zero would mean no dependency of damping on mueff, useful with CSA_disregard_length option
CSA_disregard_length : False
True is untested, also changes respective parameters
CSA_clip_length_value : None
Poorly tested, [0, 0] means const length N**0.5, [-1, 1] allows a variation of +- N/(N+2), etc.
CSA_squared : False
Use squared length for sigma-adaptation ',
BoundaryHandler : BoundTransform or BoundPenalty, unused when ``bounds in (None, [None, None])``
conditioncov_alleviate : [1e8, 1e12]
When to alleviate the condition in the coordinates and in main axes
eval_final_mean : True
Evaluate the final mean, which is a favorite return candidate
fixed_variables : None
Dictionary with index-value pairs like dict(0=1.1, 2=0.1) that are not optimized
ftarget : -inf
Target function value, minimization
integer_variables : []
Index list, invokes basic integer handling: prevent std dev to become too small in the given variables
maxfevals : inf
Maximum number of function evaluations
maxiter : 100 + 150 * (N+3)**2 // popsize**0.5
Maximum number of iterations
mean_shift_line_samples : False
Sample two new solutions colinear to previous mean shift
mindx : 0
Minimal std in any arbitrary direction, cave interference with tol
minstd : 0
Minimal std (scalar or vector) in any coordinate direction, cave interference with tol
maxstd : inf
Maximal std in any coordinate direction
pc_line_samples : False
One line sample along the evolution path pc
popsize : 4+int(3*np.log(N))
Population size, AKA lambda, number of new solution per iteration
randn : np.random.randn
Randn(lam, N) must return an np.array of shape (lam, N), see also cma.utilities.math.randhss
signals_filename : None
cma_signals.in # read versatile options from this file which contains a single options dict,
e.g. ``dict("timeout"=0)`` to stop, string-values are evaluated, e.g. "np.inf" is valid
termination_callback : None
A function returning True for termination, called in `stop` with `self` as argument, could be abused
for side effects
timeout : inf
Stop if timeout seconds are exceeded, the string "2.5 * 60**2" evaluates to 2 hours and 30 minutes
tolconditioncov : 1e14
Stop if the condition of the covariance matrix is above `tolconditioncov`
tolfacupx : 1e3
Termination when step-size increases by tolfacupx (diverges). That is, the initial step-size was chosen
far too small and better solutions were found far away from the initial solution x0
tolupsigma : 1e20
Sigma/sigma0 > tolupsigma * max(eivenvals(C)**0.5) indicates "creeping behavior" with usually minor
improvements
tolfun : 1e-11
Termination criterion: tolerance in function value, quite useful
tolfunhist : 1e-12
Termination criterion: tolerance in function value history
tolstagnation : int(100 + 100 * N**1.5 / popsize)
Termination if no improvement over tolstagnation iterations
tolx : 1e-11
Termination criterion: tolerance in x-changes
typical_x : None
Used with scaling_of_variables',
updatecovwait : None
Number of iterations without distribution update, name is subject to future changes
cmaes_verbose : 3
Verbosity e.g. of initial/final message, -1 is very quiet, -9 maximally quiet, may not be fully implemented
verb_append : 0
Initial evaluation counter, if append, do not overwrite output files
verb_disp : 100
Verbosity: display console output every verb_disp iteration
verb_filenameprefix : str
CMADataLogger.default_prefix + Output path and filenames prefix
verb_log : 1
Verbosity: write data to files every verb_log iteration, writing can be time critical on fast to
evaluate functions
verb_plot : 0
In fmin(): plot() is called every verb_plot iteration
verb_time : True
Output timings on console
vv : dict
Versatile set or dictionary for hacking purposes, value found in self.opts["vv"]
kwargs : dict
A dictionary with additional options passed to the constructor
of class ``CMAEvolutionStrategy``, see ``cma.CMAOptions`` ()
for a list of available options. | [] | def __init__(self,
x0=None,
sigma=0.1,
normalize=True,
parallelize=True,
maxfevals=np.inf,
tolfun=1e-11,
tolx=1e-11,
restarts=0,
restart_from_best='False',
incpopsize=2,
eval_initial_x=False,
noise_handler=None,
noise_change_sigma_exponent=1,
noise_kappa_exponent=0,
bipop=False,
cmaes_verbose=-9,
verb_log=0,
display=CMAESDisplay(),
**kwargs
):
"""
Parameters
----------
x0 : list or `numpy.ndarray`
initial guess of minimum solution
before the application of the geno-phenotype transformation
according to the ``transformation`` option. It can also be
a string holding a Python expression that is evaluated
to yield the initial guess - this is important in case
restarts are performed so that they start from different
places. Otherwise ``x0`` can also be a `cma.CMAEvolutionStrategy`
object instance, in that case ``sigma0`` can be ``None``.
sigma : float
Initial standard deviation in each coordinate.
``sigma0`` should be about 1/4th of the search domain width
(where the optimum is to be expected). The variables in
``objective_function`` should be scaled such that they
presumably have similar sensitivity.
See also `ScaleCoordinates`.
parallelize : bool
Whether the objective function should be called for each single evaluation or batch wise.
restarts : int, default 0
Number of restarts with increasing population size, see also
parameter ``incpopsize``, implementing the IPOP-CMA-ES restart
strategy, see also parameter ``bipop``; to restart from
different points (recommended), pass ``x0`` as a string.
restart_from_best : bool, default false
Which point to restart from
incpopsize : int
Multiplier for increasing the population size ``popsize`` before each restart
eval_initial_x : bool
Evaluate initial solution, for ``None`` only with elitist option
noise_handler : class
A ``NoiseHandler`` class or instance or ``None``. Example:
``cma.fmin(f, 6 * [1], 1, noise_handler=cma.NoiseHandler(6))``
see ``help(cma.NoiseHandler)``.
noise_change_sigma_exponent : int
Exponent for the sigma increment provided by the noise handler for
additional noise treatment. 0 means no sigma change.
noise_kappa_exponent : int
Instead of applying reevaluations, the "number of evaluations"
is (ab)used as scaling factor kappa (experimental).
bipop : bool
If `True`, run as BIPOP-CMA-ES; BIPOP is a special restart
strategy switching between two population sizings - small
(like the default CMA, but with more focused search) and
large (progressively increased as in IPOP). This makes the
algorithm perform well both on functions with many regularly
or irregularly arranged local optima (the latter by frequently
restarting with small populations). For the `bipop` parameter
to actually take effect, also select non-zero number of
(IPOP) restarts; the recommended setting is ``restarts<=9``
and `x0` passed as a string using `numpy.rand` to generate
initial solutions. Note that small-population restarts
do not count into the total restart count.
AdaptSigma : True
Or False or any CMAAdaptSigmaBase class e.g. CMAAdaptSigmaTPA, CMAAdaptSigmaCSA
CMA_active : True
Negative update, conducted after the original update
CMA_activefac : 1
Learning rate multiplier for active update
CMA_cmean : 1
Learning rate for the mean value
CMA_const_trace : False
Normalize trace, 1, True, "arithm", "geom", "aeig", "geig" are valid
CMA_diagonal : 0*100*N/popsize**0.5
Number of iterations with diagonal covariance matrix, True for always
CMA_eigenmethod : np.linalg.eigh or cma.utilities.math.eig or pygsl.eigen.eigenvectors
CMA_elitist : False or "initial" or True
Elitism likely impairs global search performance
CMA_injections_threshold_keep_len : 0
Keep length if Mahalanobis length is below the given relative threshold
CMA_mirrors : popsize < 6
Values <0.5 are interpreted as fraction, values >1 as numbers (rounded), otherwise about 0.16 is used
CMA_mirrormethod : int, default 2, 0=unconditional, 1=selective, 2=selective with delay
CMA_mu : None
Parents selection parameter, default is popsize // 2
CMA_on : 1
Multiplier for all covariance matrix updates
CMA_sampler : None
A class or instance that implements the interface of
`cma.interfaces.StatisticalModelSamplerWithZeroMeanBaseClass`
CMA_sampler_options : dict
Options passed to `CMA_sampler` class init as keyword arguments
CMA_rankmu : 1.0
Multiplier for rank-mu update learning rate of covariance matrix
CMA_rankone : 1.0
Multiplier for rank-one update learning rate of covariance matrix
CMA_recombination_weights : None
A list, see class RecombinationWeights, overwrites CMA_mu and popsize options
CMA_dampsvec_fac : np.Inf
Tentative and subject to changes, 0.5 would be a "default" damping for sigma vector update
CMA_dampsvec_fade : 0.1
Tentative fading out parameter for sigma vector update
CMA_teststds : None
Factors for non-isotropic initial distr. of C, mainly for test purpose, see CMA_stds for production
CMA_stds : None
Multipliers for sigma0 in each coordinate, not represented in C,
makes scaling_of_variables obsolete
CSA_dampfac : 1
Positive multiplier for step-size damping, 0.3 is close to optimal on the sphere
CSA_damp_mueff_exponent : 0.5
Zero would mean no dependency of damping on mueff, useful with CSA_disregard_length option
CSA_disregard_length : False
True is untested, also changes respective parameters
CSA_clip_length_value : None
Poorly tested, [0, 0] means const length N**0.5, [-1, 1] allows a variation of +- N/(N+2), etc.
CSA_squared : False
Use squared length for sigma-adaptation ',
BoundaryHandler : BoundTransform or BoundPenalty, unused when ``bounds in (None, [None, None])``
conditioncov_alleviate : [1e8, 1e12]
When to alleviate the condition in the coordinates and in main axes
eval_final_mean : True
Evaluate the final mean, which is a favorite return candidate
fixed_variables : None
Dictionary with index-value pairs like dict(0=1.1, 2=0.1) that are not optimized
ftarget : -inf
Target function value, minimization
integer_variables : []
Index list, invokes basic integer handling: prevent std dev to become too small in the given variables
maxfevals : inf
Maximum number of function evaluations
maxiter : 100 + 150 * (N+3)**2 // popsize**0.5
Maximum number of iterations
mean_shift_line_samples : False
Sample two new solutions colinear to previous mean shift
mindx : 0
Minimal std in any arbitrary direction, cave interference with tol
minstd : 0
Minimal std (scalar or vector) in any coordinate direction, cave interference with tol
maxstd : inf
Maximal std in any coordinate direction
pc_line_samples : False
One line sample along the evolution path pc
popsize : 4+int(3*np.log(N))
Population size, AKA lambda, number of new solution per iteration
randn : np.random.randn
Randn(lam, N) must return an np.array of shape (lam, N), see also cma.utilities.math.randhss
signals_filename : None
cma_signals.in # read versatile options from this file which contains a single options dict,
e.g. ``dict("timeout"=0)`` to stop, string-values are evaluated, e.g. "np.inf" is valid
termination_callback : None
A function returning True for termination, called in `stop` with `self` as argument, could be abused
for side effects
timeout : inf
Stop if timeout seconds are exceeded, the string "2.5 * 60**2" evaluates to 2 hours and 30 minutes
tolconditioncov : 1e14
Stop if the condition of the covariance matrix is above `tolconditioncov`
tolfacupx : 1e3
Termination when step-size increases by tolfacupx (diverges). That is, the initial step-size was chosen
far too small and better solutions were found far away from the initial solution x0
tolupsigma : 1e20
Sigma/sigma0 > tolupsigma * max(eivenvals(C)**0.5) indicates "creeping behavior" with usually minor
improvements
tolfun : 1e-11
Termination criterion: tolerance in function value, quite useful
tolfunhist : 1e-12
Termination criterion: tolerance in function value history
tolstagnation : int(100 + 100 * N**1.5 / popsize)
Termination if no improvement over tolstagnation iterations
tolx : 1e-11
Termination criterion: tolerance in x-changes
typical_x : None
Used with scaling_of_variables',
updatecovwait : None
Number of iterations without distribution update, name is subject to future changes
cmaes_verbose : 3
Verbosity e.g. of initial/final message, -1 is very quiet, -9 maximally quiet, may not be fully implemented
verb_append : 0
Initial evaluation counter, if append, do not overwrite output files
verb_disp : 100
Verbosity: display console output every verb_disp iteration
verb_filenameprefix : str
CMADataLogger.default_prefix + Output path and filenames prefix
verb_log : 1
Verbosity: write data to files every verb_log iteration, writing can be time critical on fast to
evaluate functions
verb_plot : 0
In fmin(): plot() is called every verb_plot iteration
verb_time : True
Output timings on console
vv : dict
Versatile set or dictionary for hacking purposes, value found in self.opts["vv"]
kwargs : dict
A dictionary with additional options passed to the constructor
of class ``CMAEvolutionStrategy``, see ``cma.CMAOptions`` ()
for a list of available options.
"""
super().__init__(x0=x0, display=display, **kwargs)
self.es = None
self.cma = None
self.normalize = normalize
self.norm = None
self.sigma = sigma
self.restarts = restarts
self.restart_from_best = restart_from_best
self.incpopsize = incpopsize
self.eval_initial_x = eval_initial_x
self.noise_handler = noise_handler
self.noise_change_sigma_exponent = noise_change_sigma_exponent
self.noise_kappa_exponent = noise_kappa_exponent
self.bipop = bipop
self.options = dict(
verbose=cmaes_verbose,
verb_log=verb_log,
maxfevals=maxfevals,
tolfun=tolfun,
tolx=tolx,
**kwargs
)
self.default_termination = NoTermination()
self.send_array_to_yield = True
self.parallelize = parallelize
self.al = None | [
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tanjiti/packet_analysis | 457008a3e37a67b18be99dbf178ee78d5b0820c4 | protocol_parse/mysqlauth.py | python | MySQLAuth.__parse_client_data | (self, sep='\x00') | return auth_detail | :return: | [] | def __parse_client_data(self, sep='\x00'):
"""
:return:
"""
auth_detail = []
data_c2s_data_list = self.__split_mysql_data(self.data_c2s)
for item in data_c2s_data_list:
# 1. find Login Request
len_of_data_c2s = len(item)
if len_of_data_c2s < 36:
# packet header: 4
# client capabilities: 4
# max packet: 4
# charset: 1
# reserved : 23
continue
packetnumber = item[3]
# make sure the packet number is 1
if packetnumber != "01":
continue
# make sure the reserved 23 byte is all 00
is_reserved_ok = 1
for i in item[13:36]:
if i != "00":
is_reserved_ok = 0
break
if is_reserved_ok != 1:
continue
client_capabilities = bin(int("".join([item[5], item[4]]), base=16))
is_ssl = client_capabilities[-12]
# check is connect db
is_connect_db = client_capabilities[-4]
# check if swith to ssl after handshake
if len_of_data_c2s == 36:
if is_ssl == '1':
self.is_ssl = True
logging.debug(
"[MYSQL_SSL]: %s:%s -> %s:%s %f %f" % (self.src_ip, self.src_port, self.dst_ip,
self.dst_port, self.ts_start, self.ts_end))
continue
# get the user name
# string end with 00
user = ""
db = ""
pos_00 = 0
for i in range(36, len_of_data_c2s):
if item[i] == "00":
pos_00 = i
break
user = user + chr(int(item[i], base=16))
len_of_passwd = int(item[pos_00 + 1], base=16)
passwd = ""
if len_of_passwd > 0:
passwd = "".join(item[pos_00 + 2:pos_00 + 2 + len_of_passwd + 1])
if is_connect_db == '1':
pos_of_db = pos_00 + 1 + len_of_passwd + 1
for i in range(pos_of_db, len_of_data_c2s):
if item[i] == "00":
break
db = db + chr(int(item[i], base=16))
# user/database_name
crack_detail = "%s%s%s%s%s%s" % (sep, user, sep, passwd, sep, db)
auth_detail.append(crack_detail)
return auth_detail | [
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"#... | https://github.com/tanjiti/packet_analysis/blob/457008a3e37a67b18be99dbf178ee78d5b0820c4/protocol_parse/mysqlauth.py#L101-L182 | ||
gramps-project/gramps | 04d4651a43eb210192f40a9f8c2bad8ee8fa3753 | gramps/plugins/tool/verify.py | python | Disconnected.broken | (self) | return (len(self.obj.get_parent_family_handle_list())
+ len(self.obj.get_family_handle_list()) == 0) | return boolean indicating whether this rule is violated | return boolean indicating whether this rule is violated | [
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] | def broken(self):
""" return boolean indicating whether this rule is violated """
return (len(self.obj.get_parent_family_handle_list())
+ len(self.obj.get_family_handle_list()) == 0) | [
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peering-manager/peering-manager | 62c870fb9caa6dfc056feb77c595d45bc3c4988a | peeringdb/filters.py | python | NetworkIXLanFilterSet.search | (self, queryset, name, value) | return queryset.filter(qs_filter) | [] | def search(self, queryset, name, value):
if not value.strip():
return queryset
qs_filter = Q(net__name__icontains=value)
try:
qs_filter |= Q(asn=int(value.strip()))
except ValueError:
pass
return queryset.filter(qs_filter) | [
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ericflo/django-pagination | d1a8f0f9fb21c5aa14c76e2f872d8eca13e5244d | pagination/paginator.py | python | FinitePage.has_next | (self) | return True | Checks for one more item than last on this page. | Checks for one more item than last on this page. | [
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"""
Checks for one more item than last on this page.
"""
try:
next_item = self.paginator.object_list[self.paginator.per_page]
except IndexError:
return False
return True | [
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jgagneastro/coffeegrindsize | 22661ebd21831dba4cf32bfc6ba59fe3d49f879c | App/dist/coffeegrindsize.app/Contents/Resources/lib/python3.7/matplotlib/axes/_base.py | python | _AxesBase.set_axis_on | (self) | Turn the x- and y-axis on.
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] | def set_axis_on(self):
"""
Turn the x- and y-axis on.
This affects the axis lines, ticks, ticklabels, grid and axis labels.
"""
self.axison = True
self.stale = True | [
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project-alice-assistant/ProjectAlice | 9e0ba019643bdae0a5535c9fa4180739231dc361 | core/webApi/model/SkillsApi.py | python | SkillsApi.checkUpdate | (self, skillName: str) | return jsonify(success=True) | check for updates for the specified skill
:param skillName:
:return: | check for updates for the specified skill
:param skillName:
:return: | [
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"""
check for updates for the specified skill
:param skillName:
:return:
"""
if skillName not in self.SkillManager.allSkills:
return self.skillNotFound()
update = self.SkillManager.checkForSkillUpdates(skillToCheck=skillName)
if update:
self.SkillManager.updateSkills(skills=update)
return jsonify(success=True) | [
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holzschu/Carnets | 44effb10ddfc6aa5c8b0687582a724ba82c6b547 | Library/lib/python3.7/site-packages/pip/_vendor/html5lib/treewalkers/base.py | python | TreeWalker.unknown | (self, nodeType) | return self.error("Unknown node type: " + nodeType) | Handles unknown node types | Handles unknown node types | [
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] | def unknown(self, nodeType):
"""Handles unknown node types"""
return self.error("Unknown node type: " + nodeType) | [
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nccgroup/BLESuite | 0e2e534f7d9beaa8e9d76223959a60b064f61e22 | blesuite/gatt_procedures.py | python | gatt_procedure_discover_primary_services | (connection_manager, connection, device) | return device | Scans device associated with BLEConnection for all primary services
and stores them in the provided BLEDevice.
:param connection_manager: BLEConnectionManager that can send request to the peer device associated with the supplied connection.
:type connection_manager: BLEConnectionManager
:param connection: BLEConnection that is associated with the target peer device
:type connection: BLEConnection
:param device: BLEDevice object that represents the peer device
:type device: BLEDevice
:return: Poplulated BLEDevice
:rtype: BLEDevice | Scans device associated with BLEConnection for all primary services
and stores them in the provided BLEDevice. | [
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] | def gatt_procedure_discover_primary_services(connection_manager, connection, device):
"""
Scans device associated with BLEConnection for all primary services
and stores them in the provided BLEDevice.
:param connection_manager: BLEConnectionManager that can send request to the peer device associated with the supplied connection.
:type connection_manager: BLEConnectionManager
:param connection: BLEConnection that is associated with the target peer device
:type connection: BLEConnection
:param device: BLEDevice object that represents the peer device
:type device: BLEDevice
:return: Poplulated BLEDevice
:rtype: BLEDevice
"""
from blesuite.pybt.gatt import UUID
import struct
bluetooth_base_addr = "00000000-0000-1000-8000-00805F9B34FB".replace('-', '')
next_start_handle = 0x0001
connection_handle = connection.connection_handle
while True:
if not connection_manager.is_connected(connection):
logger.debug("Primary service discovery: device not connected! Reconnecting...")
connection_manager.connect(connection)
request = connection_manager.stack_connection.read_by_group_type_sync(next_start_handle, 0xffff, UUID(0x2800),
connection_handle)
if request.has_error():
logger.debug("Primary service discovery error when reading from handle:%s, "
"continuing" % hex(next_start_handle))
break
logger.debug("Response received. Stored packet len: %s", request.response.pkt.length)
length = request.response.pkt.length
service_data = request.response.pkt.data
next_start_handle = None
if length == 6: # 4 byte uuid, 2 2-byte handles
logger.debug("We've got services with 16-bit UUIDs!")
services = []
i = 0
end_loop = False
while i < len(service_data):
services.append(service_data[i:i+6])
i += 6
# print "Services:", services
for service in services:
start = struct.unpack("<h", service[:2])[0]
end = struct.unpack("<h", service[2:4])[0]
uuid_16 = struct.unpack("<h", service[4:])[0]
conversion = (uuid_16 * (2 ** 96)) + int(bluetooth_base_addr, 16)
uuid_128 = struct.pack(">QQ", (conversion >> 64) & 0xFFFFFFFFFFFFFFFF,
conversion & 0xFFFFFFFFFFFFFFFF).encode('hex')
uuid_128 = '-'.join((uuid_128[:8], uuid_128[8:12], uuid_128[12:16], uuid_128[16:20], uuid_128[20:]))
if end == -1:
end = 0xffff
if start == -1:
start = 0xffff
device.add_service(start, end, uuid_128)
if end >= 0xFFFF or end < 0:
end_loop = True
if next_start_handle is None or end >= next_start_handle:
next_start_handle = end + 1
if end_loop:
logger.debug("End of primary service discovery!")
break
elif length == 20: # 16 byte uuid, 2 2-byte handles
logger.debug("We've got services with 128-bit UUIDs!")
start = struct.unpack("<h", service_data[:2])[0]
end = struct.unpack("<h", service_data[2:4])[0]
uuid_128 = struct.unpack("<QQ", service_data[4:])
uuid_128 = "%016x%016x" % (uuid_128[1], uuid_128[0])
# print "UUID128:", uuid_128
uuid_128 = '-'.join((uuid_128[:8], uuid_128[8:12], uuid_128[12:16], uuid_128[16:20], uuid_128[20:]))
if end == -1:
end = 0xffff
if start == -1:
start = 0xffff
device.add_service(start, end, uuid_128)
if end >= 0xFFFF or end < 0:
logger.debug("End of primary service discovery!")
break
next_start_handle = end + 1
else:
logger.error("UNEXPECTED PRIMARY SERVICE DISCOVERY RESPONSE. BAILING")
break
return device | [
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RexYing/diffpool | 8dfb97cf60c2376ac804761837b9966f1d302acb | gen/feat.py | python | GaussianFeatureGen.__init__ | (self, mu, sigma) | [] | def __init__(self, mu, sigma):
self.mu = mu
self.sigma = sigma | [
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hydroshare/hydroshare | 7ba563b55412f283047fb3ef6da367d41dec58c6 | hs_tools_resource/app_launch_helper.py | python | get_app_dict | (user, resource, default_resource_term_dict) | return [default_resource_term_dict, hs_term_dict_user, hs_term_dict_file] | [] | def get_app_dict(user, resource, default_resource_term_dict):
hs_term_dict_user = {}
hs_term_dict_user["HS_USR_NAME"] = user.username if user.is_authenticated() else "anonymous"
hs_term_dict_file = {}
# HS_JS_AGG_KEY and HS_JS_FILE_KEY are overwritten by jquery to launch the url specific to each
# file
hs_term_dict_file["HS_AGG_PATH"] = "HS_JS_AGG_KEY"
hs_term_dict_file["HS_FILE_PATH"] = "HS_JS_FILE_KEY"
hs_term_dict_file["HS_MAIN_FILE"] = "HS_JS_MAIN_FILE_KEY"
default_resource_term_dict.update(resource.get_hs_term_dict())
return [default_resource_term_dict, hs_term_dict_user, hs_term_dict_file] | [
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VirtueSecurity/aws-extender | d123b7e1a845847709ba3a481f11996bddc68a1c | BappModules/boto/iam/connection.py | python | IAMConnection.list_instance_profiles_for_role | (self, role_name, marker=None,
max_items=None) | return self.get_response('ListInstanceProfilesForRole', params,
list_marker='InstanceProfiles') | Lists the instance profiles that have the specified associated role. If
there are none, the action returns an empty list.
:type role_name: string
:param role_name: The name of the role to list instance profiles for.
:type marker: string
:param marker: Use this parameter only when paginating results, and
only in a subsequent request after you've received a response
where the results are truncated. Set it to the value of the
Marker element in the response you just received.
:type max_items: int
:param max_items: Use this parameter only when paginating results to
indicate the maximum number of user names you want in the response. | Lists the instance profiles that have the specified associated role. If
there are none, the action returns an empty list. | [
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] | def list_instance_profiles_for_role(self, role_name, marker=None,
max_items=None):
"""
Lists the instance profiles that have the specified associated role. If
there are none, the action returns an empty list.
:type role_name: string
:param role_name: The name of the role to list instance profiles for.
:type marker: string
:param marker: Use this parameter only when paginating results, and
only in a subsequent request after you've received a response
where the results are truncated. Set it to the value of the
Marker element in the response you just received.
:type max_items: int
:param max_items: Use this parameter only when paginating results to
indicate the maximum number of user names you want in the response.
"""
params = {'RoleName': role_name}
if marker is not None:
params['Marker'] = marker
if max_items is not None:
params['MaxItems'] = max_items
return self.get_response('ListInstanceProfilesForRole', params,
list_marker='InstanceProfiles') | [
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