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ym2011/POC-EXP | 206b22d3a6b2a172359678df33bbc5b2ad04b6c3 | K8/Web-Exp/sqlmap/lib/techniques/error/use.py | python | _formatPartialContent | (value) | return value | Prepares (possibly hex-encoded) partial content for safe console output | Prepares (possibly hex-encoded) partial content for safe console output | [
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"(",
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"hex",
"-",
"encoded",
")",
"partial",
"content",
"for",
"safe",
"console",
"output"
] | def _formatPartialContent(value):
"""
Prepares (possibly hex-encoded) partial content for safe console output
"""
if value and isinstance(value, basestring):
try:
value = hexdecode(value)
except:
pass
finally:
value = safecharencode(value)
return value | [
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microsoft/unilm | 65f15af2a307ebb64cfb25adf54375b002e6fe8d | infoxlm/fairseq/examples/roberta/multiprocessing_bpe_encoder.py | python | MultiprocessingEncoder.encode_lines | (self, lines) | return ["PASS", enc_lines] | Encode a set of lines. All lines will be encoded together. | Encode a set of lines. All lines will be encoded together. | [
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] | def encode_lines(self, lines):
"""
Encode a set of lines. All lines will be encoded together.
"""
enc_lines = []
for line in lines:
line = line.strip()
if len(line) == 0 and not self.args.keep_empty:
return ["EMPTY", None]
tokens = self.encode(line)
enc_lines.append(" ".join(tokens))
return ["PASS", enc_lines] | [
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khanhnamle1994/natural-language-processing | 01d450d5ac002b0156ef4cf93a07cb508c1bcdc5 | assignment1/.env/lib/python2.7/site-packages/scipy/stats/stats.py | python | signaltonoise | (a, axis=0, ddof=0) | return np.where(sd == 0, 0, m/sd) | The signal-to-noise ratio of the input data.
Returns the signal-to-noise ratio of `a`, here defined as the mean
divided by the standard deviation.
Parameters
----------
a : array_like
An array_like object containing the sample data.
axis : int or None, optional
If axis is equal to None, the array is first ravel'd. If axis is an
integer, this is the axis over which to operate. Default is 0.
ddof : int, optional
Degrees of freedom correction for standard deviation. Default is 0.
Returns
-------
s2n : ndarray
The mean to standard deviation ratio(s) along `axis`, or 0 where the
standard deviation is 0. | The signal-to-noise ratio of the input data. | [
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] | def signaltonoise(a, axis=0, ddof=0):
"""
The signal-to-noise ratio of the input data.
Returns the signal-to-noise ratio of `a`, here defined as the mean
divided by the standard deviation.
Parameters
----------
a : array_like
An array_like object containing the sample data.
axis : int or None, optional
If axis is equal to None, the array is first ravel'd. If axis is an
integer, this is the axis over which to operate. Default is 0.
ddof : int, optional
Degrees of freedom correction for standard deviation. Default is 0.
Returns
-------
s2n : ndarray
The mean to standard deviation ratio(s) along `axis`, or 0 where the
standard deviation is 0.
"""
a = np.asanyarray(a)
m = a.mean(axis)
sd = a.std(axis=axis, ddof=ddof)
return np.where(sd == 0, 0, m/sd) | [
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/Python-2.7.9/Lib/idlelib/configDialog.py | python | ConfigDialog.VarChanged_winHeight | (self, *params) | [] | def VarChanged_winHeight(self, *params):
value = self.winHeight.get()
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mgear-dev/mgear | 06ddc26c5adb5eab07ca470c7fafa77404c8a1de | scripts/mgear/maya/shifter/component/shoulder_ms_01/guide.py | python | Guide.addParameters | (self) | Add the configurations settings | Add the configurations settings | [
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"configurations",
"settings"
] | def addParameters(self):
"""Add the configurations settings"""
self.pUseIndex = self.addParam("useIndex", "bool", False)
self.pParentJointIndex = self.addParam(
"parentJointIndex", "long", -1, None, None) | [
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GiulioRossetti/cdlib | b2c6311b99725bb2b029556f531d244a2af14a2a | cdlib/algorithms/crisp_partition.py | python | label_propagation | (g_original: object) | return NodeClustering(
coms, g_original, "Label Propagation", method_parameters={"": ""}
) | The Label Propagation algorithm (LPA) detects communities using network structure alone.
The algorithm doesn’t require a pre-defined objective function or prior information about the communities.
It works as follows:
-Every node is initialized with a unique label (an identifier)
-These labels propagate through the network
-At every iteration of propagation, each node updates its label to the one that the maximum numbers of its neighbours belongs to. Ties are broken uniformly and randomly.
-LPA reaches convergence when each node has the majority label of its neighbours.
**Supported Graph Types**
========== ======== ========
Undirected Directed Weighted
========== ======== ========
Yes No No
========== ======== ========
:param g_original: a networkx/igraph object
:return: EdgeClustering object
:Example:
>>> from cdlib import algorithms
>>> import networkx as nx
>>> G = nx.karate_club_graph()
>>> coms = algorithms.label_propagation(G)
:References:
Cordasco, G., & Gargano, L. (2010, December). Community detection via semi-synchronous label propagation algorithms. In 2010 IEEE international workshop on: business applications of social network analysis (BASNA) (pp. 1-8). IEEE. | The Label Propagation algorithm (LPA) detects communities using network structure alone.
The algorithm doesn’t require a pre-defined objective function or prior information about the communities.
It works as follows:
-Every node is initialized with a unique label (an identifier)
-These labels propagate through the network
-At every iteration of propagation, each node updates its label to the one that the maximum numbers of its neighbours belongs to. Ties are broken uniformly and randomly.
-LPA reaches convergence when each node has the majority label of its neighbours. | [
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"""
The Label Propagation algorithm (LPA) detects communities using network structure alone.
The algorithm doesn’t require a pre-defined objective function or prior information about the communities.
It works as follows:
-Every node is initialized with a unique label (an identifier)
-These labels propagate through the network
-At every iteration of propagation, each node updates its label to the one that the maximum numbers of its neighbours belongs to. Ties are broken uniformly and randomly.
-LPA reaches convergence when each node has the majority label of its neighbours.
**Supported Graph Types**
========== ======== ========
Undirected Directed Weighted
========== ======== ========
Yes No No
========== ======== ========
:param g_original: a networkx/igraph object
:return: EdgeClustering object
:Example:
>>> from cdlib import algorithms
>>> import networkx as nx
>>> G = nx.karate_club_graph()
>>> coms = algorithms.label_propagation(G)
:References:
Cordasco, G., & Gargano, L. (2010, December). Community detection via semi-synchronous label propagation algorithms. In 2010 IEEE international workshop on: business applications of social network analysis (BASNA) (pp. 1-8). IEEE.
"""
g = convert_graph_formats(g_original, nx.Graph)
coms = list(nx.algorithms.community.label_propagation_communities(g))
coms = [list(x) for x in coms]
return NodeClustering(
coms, g_original, "Label Propagation", method_parameters={"": ""}
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huawei-noah/vega | d9f13deede7f2b584e4b1d32ffdb833856129989 | vega/modules/operators/functions/pytorch_to_tf.py | python | assign_weights | (pt_state_dict, pretrained_prefix=None) | return [_var.assign(_value) for _var, _value in vars_values] | Load pytorch state_dict and assign to tensorflow model. | Load pytorch state_dict and assign to tensorflow model. | [
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] | def assign_weights(pt_state_dict, pretrained_prefix=None):
"""Load pytorch state_dict and assign to tensorflow model."""
import tensorflow as tf
vars = tf.get_collection(tf.GraphKeys.GLOBAL_VARIABLES)
vars.pop(0)
pt_state_dict = {k: v for k, v in pt_state_dict.items() if 'num_batches_tracked' not in k}
def _filter_vars_by_keys(var):
for key in pretrained_prefix.keys():
if var.name.startswith(key):
return True
def _filter_state_by_keys(state):
for key in pretrained_prefix.values():
if state.startswith(key):
return True
if pretrained_prefix:
vars = list(filter(_filter_vars_by_keys, vars))
pt_state_dict = {k: v for k, v in pt_state_dict.items() if _filter_state_by_keys(k)}
if not pt_state_dict or not vars:
raise ValueError("pertrained weight is None, please check the pretrained_prefix: {}".format(pretrained_prefix))
vars_values = load_weight(pt_state_dict, vars)
return [_var.assign(_value) for _var, _value in vars_values] | [
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timkpaine/tributary | 90acb236d96a23c0c4794fd0f2da82c66060f737 | tributary/streaming/output/email.py | python | make_email | (html, from_, subject="", attachments=None) | return message | Helper function to make emails
html (str): content
from_ (str): address to send the email from
subject (str): subject of email
attachments (list) : attachments to send | Helper function to make emails | [
"Helper",
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"to",
"make",
"emails"
] | def make_email(html, from_, subject="", attachments=None):
"""Helper function to make emails
html (str): content
from_ (str): address to send the email from
subject (str): subject of email
attachments (list) : attachments to send
"""
message = emails.html(charset="utf-8", subject=subject, html=html, mail_from=from_)
soup = BeautifulSoup(html, "html.parser")
# strip markdown links
for item in soup.findAll("a", {"class": "anchor-link"}):
item.decompose()
# strip matplotlib base outs
for item in soup.find_all(
"div", class_="output_text output_subarea output_execute_result"
):
for c in item.contents:
if "<matplotlib" in str(c):
item.decompose()
# remove dataframe table borders
for item in soup.findAll("table", {"border": 1}):
item["border"] = 0
item["cellspacing"] = 0
item["cellpadding"] = 0
# extract imgs for outlook
imgs = soup.find_all("img")
imgs_to_attach = {}
# attach main part
for i, img in enumerate(imgs):
if not img.get("localdata"):
continue
imgs_to_attach[img.get("cell_id") + "_" + str(i) + ".png"] = base64.b64decode(
img.get("localdata")
)
img["src"] = "cid:" + img.get("cell_id") + "_" + str(i) + ".png"
# encoders.encode_base64(part)
del img["localdata"]
# assemble email soup
soup = str(soup)
message = emails.html(charset="utf-8", subject=subject, html=soup, mail_from=from_)
for img, data in imgs_to_attach.items():
message.attach(filename=img, content_disposition="inline", data=data)
return message | [
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dansanderson/picotool | d8c51e58416f8010dc8c0fba3df5f0424b5bb852 | pico8/util.py | python | BaseSection.to_lines | (self) | Generates lines of ASCII-encoded hexadecimal strings.
Yields:
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Yields:
One line of a hex string.
"""
for start_i in range(0, len(self._data), self.HEX_LINE_LENGTH_BYTES):
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if end_i > len(self._data):
end_i = len(self._data)
yield bytes(bytes_to_hex(bytes(self._data[start_i:end_i])),
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ninja-ide/ninja-ide | 87d91131bd19fdc3dcfd91eb97ad1e41c49c60c0 | ninja_ide/gui/ide.py | python | IDE.change_toolsdock_visibility | (self) | Switch the tools dock visibility | Switch the tools dock visibility | [
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"""Switch the tools dock visibility"""
tools_dock = IDE.get_service("tools_dock").buttons_widget
if tools_dock.isVisible():
tools_dock.hide()
else:
tools_dock.show() | [
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cclib/cclib | 81cd4a81cc4a3bbed7016b3e417ca9bff8ad3a92 | cclib/parser/qchemparser.py | python | QChem.generate_formula_histogram | (self) | return histogram | From the atomnos, generate a histogram that represents the
molecular formula. | From the atomnos, generate a histogram that represents the
molecular formula. | [
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"""
histogram = dict()
for element in self.atomelements:
if element in histogram.keys():
histogram[element] += 1
else:
histogram[element] = 1
return histogram | [
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securesystemslab/zippy | ff0e84ac99442c2c55fe1d285332cfd4e185e089 | zippy/lib-python/3/datetime.py | python | datetime.__repr__ | (self) | return s | Convert to formal string, for repr(). | Convert to formal string, for repr(). | [
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] | def __repr__(self):
"""Convert to formal string, for repr()."""
L = [self._year, self._month, self._day, # These are never zero
self._hour, self._minute, self._second, self._microsecond]
if L[-1] == 0:
del L[-1]
if L[-1] == 0:
del L[-1]
s = ", ".join(map(str, L))
s = "%s(%s)" % ('datetime.' + self.__class__.__name__, s)
if self._tzinfo is not None:
assert s[-1:] == ")"
s = s[:-1] + ", tzinfo=%r" % self._tzinfo + ")"
return s | [
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Azure/azure-devops-cli-extension | 11334cd55806bef0b99c3bee5a438eed71e44037 | azure-devops/azext_devops/devops_sdk/v6_0/feature_management/feature_management_client.py | python | FeatureManagementClient.get_features | (self, target_contribution_id=None) | return self._deserialize('[ContributedFeature]', self._unwrap_collection(response)) | GetFeatures.
[Preview API] Get a list of all defined features
:param str target_contribution_id: Optional target contribution. If null/empty, return all features. If specified include the features that target the specified contribution.
:rtype: [ContributedFeature] | GetFeatures.
[Preview API] Get a list of all defined features
:param str target_contribution_id: Optional target contribution. If null/empty, return all features. If specified include the features that target the specified contribution.
:rtype: [ContributedFeature] | [
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"""GetFeatures.
[Preview API] Get a list of all defined features
:param str target_contribution_id: Optional target contribution. If null/empty, return all features. If specified include the features that target the specified contribution.
:rtype: [ContributedFeature]
"""
query_parameters = {}
if target_contribution_id is not None:
query_parameters['targetContributionId'] = self._serialize.query('target_contribution_id', target_contribution_id, 'str')
response = self._send(http_method='GET',
location_id='c4209f25-7a27-41dd-9f04-06080c7b6afd',
version='6.0-preview.1',
query_parameters=query_parameters)
return self._deserialize('[ContributedFeature]', self._unwrap_collection(response)) | [
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KvasirSecurity/Kvasir | a5b3775184a8343240e1154a1f762f75df04dc0a | controllers/hosts.py | python | mass_vulndata | () | Add a vulndata to a lot of hosts
TODO: This! | Add a vulndata to a lot of hosts
TODO: This! | [
"Add",
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"vulndata",
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"a",
"lot",
"of",
"hosts",
"TODO",
":",
"This!"
] | def mass_vulndata():
"""
Add a vulndata to a lot of hosts
TODO: This!
"""
host_ids = []
if request.vars.has_key('host_ids'):
for z in request.vars.host_ids.split('|'):
if z is not '':
host_ids.append(z)
form=SQLFORM.factory(
Field('vulndata', 'reference t_vulndata', label=T('Vulnerability')),
buttons=[], _id="mass_asset_form")
if form.validate():
pass | [
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... | https://github.com/KvasirSecurity/Kvasir/blob/a5b3775184a8343240e1154a1f762f75df04dc0a/controllers/hosts.py#L746-L762 | ||
dimagi/commcare-hq | d67ff1d3b4c51fa050c19e60c3253a79d3452a39 | corehq/apps/fixtures/models.py | python | FixtureDataItem.remove_group | (self, group) | return self.remove_owner(group, 'group') | [] | def remove_group(self, group):
return self.remove_owner(group, 'group') | [
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Source-Python-Dev-Team/Source.Python | d0ffd8ccbd1e9923c9bc44936f20613c1c76b7fb | addons/source-python/Python3/operator.py | python | ixor | (a, b) | return a | Same as a ^= b. | Same as a ^= b. | [
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a ^= b
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HymanLiuTS/flaskTs | 286648286976e85d9b9a5873632331efcafe0b21 | flasky/lib/python2.7/site-packages/selenium/webdriver/common/action_chains.py | python | ActionChains.context_click | (self, on_element=None) | return self | Performs a context-click (right click) on an element.
:Args:
- on_element: The element to context-click.
If None, clicks on current mouse position. | Performs a context-click (right click) on an element. | [
"Performs",
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"-",
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"(",
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] | def context_click(self, on_element=None):
"""
Performs a context-click (right click) on an element.
:Args:
- on_element: The element to context-click.
If None, clicks on current mouse position.
"""
if on_element:
self.move_to_element(on_element)
self._actions.append(lambda: self._driver.execute(
Command.CLICK, {'button': 2}))
return self | [
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realpython/book2-exercises | cde325eac8e6d8cff2316601c2e5b36bb46af7d0 | web2py/venv/lib/python2.7/site-packages/pip/utils/__init__.py | python | ask | (message, options) | Ask the message interactively, with the given possible responses | Ask the message interactively, with the given possible responses | [
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] | def ask(message, options):
"""Ask the message interactively, with the given possible responses"""
while 1:
if os.environ.get('PIP_NO_INPUT'):
raise Exception(
'No input was expected ($PIP_NO_INPUT set); question: %s' %
message
)
response = input(message)
response = response.strip().lower()
if response not in options:
print(
'Your response (%r) was not one of the expected responses: '
'%s' % (response, ', '.join(options))
)
else:
return response | [
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wistbean/learn_python3_spider | 73c873f4845f4385f097e5057407d03dd37a117b | stackoverflow/venv/lib/python3.6/site-packages/pymongo/message.py | python | _batched_op_msg_impl | (
operation, command, docs, check_keys, ack, opts, ctx, buf) | return to_send, length | Create a batched OP_MSG write. | Create a batched OP_MSG write. | [
"Create",
"a",
"batched",
"OP_MSG",
"write",
"."
] | def _batched_op_msg_impl(
operation, command, docs, check_keys, ack, opts, ctx, buf):
"""Create a batched OP_MSG write."""
max_bson_size = ctx.max_bson_size
max_write_batch_size = ctx.max_write_batch_size
max_message_size = ctx.max_message_size
flags = b"\x00\x00\x00\x00" if ack else b"\x02\x00\x00\x00"
# Flags
buf.write(flags)
# Type 0 Section
buf.write(b"\x00")
buf.write(_dict_to_bson(command, False, opts))
# Type 1 Section
buf.write(b"\x01")
size_location = buf.tell()
# Save space for size
buf.write(b"\x00\x00\x00\x00")
try:
buf.write(_OP_MSG_MAP[operation])
except KeyError:
raise InvalidOperation('Unknown command')
if operation in (_UPDATE, _DELETE):
check_keys = False
to_send = []
idx = 0
for doc in docs:
# Encode the current operation
value = _dict_to_bson(doc, check_keys, opts)
doc_length = len(value)
new_message_size = buf.tell() + doc_length
# Does first document exceed max_message_size?
doc_too_large = (idx == 0 and (new_message_size > max_message_size))
# When OP_MSG is used unacknowleged we have to check
# document size client side or applications won't be notified.
# Otherwise we let the server deal with documents that are too large
# since ordered=False causes those documents to be skipped instead of
# halting the bulk write operation.
unacked_doc_too_large = (not ack and (doc_length > max_bson_size))
if doc_too_large or unacked_doc_too_large:
write_op = list(_FIELD_MAP.keys())[operation]
_raise_document_too_large(
write_op, len(value), max_bson_size)
# We have enough data, return this batch.
if new_message_size > max_message_size:
break
buf.write(value)
to_send.append(doc)
idx += 1
# We have enough documents, return this batch.
if idx == max_write_batch_size:
break
# Write type 1 section size
length = buf.tell()
buf.seek(size_location)
buf.write(_pack_int(length - size_location))
return to_send, length | [
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IJDykeman/wangTiles | 7c1ee2095ebdf7f72bce07d94c6484915d5cae8b | experimental_code/tiles_3d/venv_mac/lib/python2.7/site-packages/pip/_vendor/pkg_resources/__init__.py | python | WorkingSet.subscribe | (self, callback, existing=True) | Invoke `callback` for all distributions
If `existing=True` (default),
call on all existing ones, as well. | Invoke `callback` for all distributions | [
"Invoke",
"callback",
"for",
"all",
"distributions"
] | def subscribe(self, callback, existing=True):
"""Invoke `callback` for all distributions
If `existing=True` (default),
call on all existing ones, as well.
"""
if callback in self.callbacks:
return
self.callbacks.append(callback)
if not existing:
return
for dist in self:
callback(dist) | [
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GoogleCloudPlatform/PerfKitBenchmarker | 6e3412d7d5e414b8ca30ed5eaf970cef1d919a67 | perfkitbenchmarker/linux_benchmarks/unixbench_benchmark.py | python | Cleanup | (benchmark_spec) | Cleanup UnixBench on the target vm.
Args:
benchmark_spec: The benchmark specification. Contains all data that is
required to run the benchmark. | Cleanup UnixBench on the target vm. | [
"Cleanup",
"UnixBench",
"on",
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"target",
"vm",
"."
] | def Cleanup(benchmark_spec):
"""Cleanup UnixBench on the target vm.
Args:
benchmark_spec: The benchmark specification. Contains all data that is
required to run the benchmark.
"""
pass | [
"def",
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pyansys/pymapdl | c07291fc062b359abf0e92b95a92d753a95ef3d7 | ansys/mapdl/core/_commands/post1_/animation.py | python | Animation.andata | (
self,
delay="",
ncycl="",
rsltdat="",
min_="",
max_="",
incr="",
frclst="",
autocont="",
autocntr="",
**kwargs,
) | return self.run(command, **kwargs) | Displays animated graphics data for nonlinear problems.
APDL Command: ANDATA
Parameters
----------
delay
Time delay during animation (defaults to 0.5 seconds).
ncycl
Number of animation cycles (defaults to 5). Available in non-UI
mode only.
rsltdat
The type of results data to be used for the animation sequence.
This can be:
0 - Current load step data (default).
1 - Range of load step data.
2 - Range of results data.
min\_
The range minimum value. If left blank or 0, defaults to the first
data point.
max\_
The range maximum value. If left blank or 0, defaults to the last
data point.
incr
The increment between result data (defaults to 1).
frclst
Key to force the last sub step in a selected load step to be
included in the animation (defaults to 0).
autocont
A value of 1 enables automatic scaling of contour values based on
the overall subset range of values. The default value is 0 (no
automatic scaling).
autocntr
A value of 1 disables automatic centering of displaced plots. The
default value is 0 (allow automatic centering).
Notes
-----
Use the ANDATA command to create animations for nonlinear problems. The
command works by displaying an individual graphical image for each
result data set from the results file. For information about creating
animations for linear problems, see the ANIM command.
The command operates only on graphic display platforms supporting the
/SEG command. It uses a macro to produce an animation based on the last
plot action command (for example, PLDISP).
The results file must have more than one set of results.
The command implicitly issues /DSCALE, 1 for default displacement
scaling. Large displacements may not give good results.
This command functions only in the postprocessor. | Displays animated graphics data for nonlinear problems. | [
"Displays",
"animated",
"graphics",
"data",
"for",
"nonlinear",
"problems",
"."
] | def andata(
self,
delay="",
ncycl="",
rsltdat="",
min_="",
max_="",
incr="",
frclst="",
autocont="",
autocntr="",
**kwargs,
):
"""Displays animated graphics data for nonlinear problems.
APDL Command: ANDATA
Parameters
----------
delay
Time delay during animation (defaults to 0.5 seconds).
ncycl
Number of animation cycles (defaults to 5). Available in non-UI
mode only.
rsltdat
The type of results data to be used for the animation sequence.
This can be:
0 - Current load step data (default).
1 - Range of load step data.
2 - Range of results data.
min\_
The range minimum value. If left blank or 0, defaults to the first
data point.
max\_
The range maximum value. If left blank or 0, defaults to the last
data point.
incr
The increment between result data (defaults to 1).
frclst
Key to force the last sub step in a selected load step to be
included in the animation (defaults to 0).
autocont
A value of 1 enables automatic scaling of contour values based on
the overall subset range of values. The default value is 0 (no
automatic scaling).
autocntr
A value of 1 disables automatic centering of displaced plots. The
default value is 0 (allow automatic centering).
Notes
-----
Use the ANDATA command to create animations for nonlinear problems. The
command works by displaying an individual graphical image for each
result data set from the results file. For information about creating
animations for linear problems, see the ANIM command.
The command operates only on graphic display platforms supporting the
/SEG command. It uses a macro to produce an animation based on the last
plot action command (for example, PLDISP).
The results file must have more than one set of results.
The command implicitly issues /DSCALE, 1 for default displacement
scaling. Large displacements may not give good results.
This command functions only in the postprocessor.
"""
command = f"ANDATA,{delay},{ncycl},{rsltdat},{min_},{max_},{incr},{frclst},{autocont},,{autocntr}"
return self.run(command, **kwargs) | [
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rwightman/gen-efficientnet-pytorch | 2d6623e956fbc9ac9c2f86ace2619e22ce7e2960 | geffnet/gen_efficientnet.py | python | efficientnet_lite3 | (pretrained=False, **kwargs) | return model | EfficientNet-Lite3 | EfficientNet-Lite3 | [
"EfficientNet",
"-",
"Lite3"
] | def efficientnet_lite3(pretrained=False, **kwargs):
""" EfficientNet-Lite3 """
model = _gen_efficientnet_lite(
'efficientnet_lite3', channel_multiplier=1.2, depth_multiplier=1.4, pretrained=pretrained, **kwargs)
return model | [
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phonopy/phonopy | 816586d0ba8177482ecf40e52f20cbdee2260d51 | phonopy/harmonic/dynamical_matrix.py | python | DynamicalMatrixGL._get_c_recip_dipole_dipole | (self, q_cart, q_dir_cart) | return dd | Reciprocal part of Eq.(71) on the right hand side.
This is subtracted from supercell force constants to create
short-range force constants. Only once at commensurate points.
This is added to interpolated short range force constants
to create full force constants. Called many times. | Reciprocal part of Eq.(71) on the right hand side. | [
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"of",
"Eq",
".",
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"71",
")",
"on",
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] | def _get_c_recip_dipole_dipole(self, q_cart, q_dir_cart):
"""Reciprocal part of Eq.(71) on the right hand side.
This is subtracted from supercell force constants to create
short-range force constants. Only once at commensurate points.
This is added to interpolated short range force constants
to create full force constants. Called many times.
"""
import phonopy._phonopy as phonoc
pos = self._pcell.positions
num_atom = len(pos)
volume = self._pcell.volume
dd = np.zeros((num_atom, 3, num_atom, 3), dtype=self._dtype_complex, order="C")
phonoc.recip_dipole_dipole(
dd.view(dtype="double"),
self._dd_q0.view(dtype="double"),
self._G_list,
q_cart,
q_dir_cart,
self._born,
self._dielectric,
np.array(pos, dtype="double", order="C"),
self._unit_conversion * 4.0 * np.pi / volume,
self._Lambda,
self._symprec,
)
return dd | [
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securesystemslab/zippy | ff0e84ac99442c2c55fe1d285332cfd4e185e089 | zippy/benchmarks/src/benchmarks/sympy/sympy/matrices/expressions/matpow.py | python | MatPow._entry | (self, i, j) | [] | def _entry(self, i, j):
if self.exp.is_Integer:
# Make an explicity MatMul out of the MatPow
return MatMul(*[self.base for k in range(self.exp)])._entry(i, j) | [
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TencentCloud/tencentcloud-sdk-python | 3677fd1cdc8c5fd626ce001c13fd3b59d1f279d2 | tencentcloud/vod/v20180717/vod_client.py | python | VodClient.ModifySubAppIdInfo | (self, request) | 该接口用于修改子应用信息，但不允许修改主应用信息。
:param request: Request instance for ModifySubAppIdInfo.
:type request: :class:`tencentcloud.vod.v20180717.models.ModifySubAppIdInfoRequest`
:rtype: :class:`tencentcloud.vod.v20180717.models.ModifySubAppIdInfoResponse` | 该接口用于修改子应用信息，但不允许修改主应用信息。 | [
"该接口用于修改子应用信息，但不允许修改主应用信息。"
] | def ModifySubAppIdInfo(self, request):
"""该接口用于修改子应用信息，但不允许修改主应用信息。
:param request: Request instance for ModifySubAppIdInfo.
:type request: :class:`tencentcloud.vod.v20180717.models.ModifySubAppIdInfoRequest`
:rtype: :class:`tencentcloud.vod.v20180717.models.ModifySubAppIdInfoResponse`
"""
try:
params = request._serialize()
body = self.call("ModifySubAppIdInfo", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.ModifySubAppIdInfoResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message) | [
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ni/nidaqmx-python | 62fc6b48cbbb330fe1bcc9aedadc86610a1269b6 | nidaqmx/_task_modules/timing.py | python | Timing.samp_clk_timebase_active_edge | (self) | return Edge(val.value) | :class:`nidaqmx.constants.Edge`: Specifies on which edge to
recognize a Sample Clock Timebase pulse. This property is
useful primarily when the signal you use as the Sample Clock
Timebase is not a periodic clock. | :class:`nidaqmx.constants.Edge`: Specifies on which edge to
recognize a Sample Clock Timebase pulse. This property is
useful primarily when the signal you use as the Sample Clock
Timebase is not a periodic clock. | [
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"""
:class:`nidaqmx.constants.Edge`: Specifies on which edge to
recognize a Sample Clock Timebase pulse. This property is
useful primarily when the signal you use as the Sample Clock
Timebase is not a periodic clock.
"""
val = ctypes.c_int()
cfunc = lib_importer.windll.DAQmxGetSampClkTimebaseActiveEdge
if cfunc.argtypes is None:
with cfunc.arglock:
if cfunc.argtypes is None:
cfunc.argtypes = [
lib_importer.task_handle, ctypes.POINTER(ctypes.c_int)]
error_code = cfunc(
self._handle, ctypes.byref(val))
check_for_error(error_code)
return Edge(val.value) | [
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n0fate/chainbreaker | 6f5a2c74bb922769e2f3d05f7ead6f36d2750277 | pyDes.py | python | DES.__des_crypt | (self, block, crypt_type) | return self.final | Crypt the block of data through DES bit-manipulation | Crypt the block of data through DES bit-manipulation | [
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"""Crypt the block of data through DES bit-manipulation"""
block = self.__permutate(DES.__ip, block)
self.L = block[:32]
self.R = block[32:]
# Encryption starts from Kn[1] through to Kn[16]
if crypt_type == DES.ENCRYPT:
iteration = 0
iteration_adjustment = 1
# Decryption starts from Kn[16] down to Kn[1]
else:
iteration = 15
iteration_adjustment = -1
i = 0
while i < 16:
# Make a copy of R[i-1], this will later become L[i]
tempR = self.R[:]
# Permutate R[i - 1] to start creating R[i]
self.R = self.__permutate(DES.__expansion_table, self.R)
# Exclusive or R[i - 1] with K[i], create B[1] to B[8] whilst here
self.R = map(lambda x, y: x ^ y, self.R, self.Kn[iteration])
B = [self.R[:6], self.R[6:12], self.R[12:18], self.R[18:24], self.R[24:30], self.R[30:36], self.R[36:42],
self.R[42:]]
# Optimization: Replaced below commented code with above
# j = 0
# B = []
# while j < len(self.R):
# self.R[j] = self.R[j] ^ self.Kn[iteration][j]
# j += 1
# if j % 6 == 0:
# B.append(self.R[j-6:j])
# Permutate B[1] to B[8] using the S-Boxes
j = 0
Bn = [0] * 32
pos = 0
while j < 8:
# Work out the offsets
m = (B[j][0] << 1) + B[j][5]
n = (B[j][1] << 3) + (B[j][2] << 2) + (B[j][3] << 1) + B[j][4]
# Find the permutation value
v = DES.__sbox[j][(m << 4) + n]
# Turn value into bits, add it to result: Bn
Bn[pos] = (v & 8) >> 3
Bn[pos + 1] = (v & 4) >> 2
Bn[pos + 2] = (v & 2) >> 1
Bn[pos + 3] = v & 1
pos += 4
j += 1
# Permutate the concatination of B[1] to B[8] (Bn)
self.R = self.__permutate(DES.__p, Bn)
# Xor with L[i - 1]
self.R = map(lambda x, y: x ^ y, self.R, self.L)
# Optimization: This now replaces the below commented code
# j = 0
# while j < len(self.R):
# self.R[j] = self.R[j] ^ self.L[j]
# j += 1
# L[i] becomes R[i - 1]
self.L = tempR
i += 1
iteration += iteration_adjustment
# Final permutation of R[16]L[16]
self.final = self.__permutate(DES.__fp, self.R + self.L)
return self.final | [
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khast3x/h8mail | 0a371eb2e6ff786865e6608e46ee3ac5103a4dbc | h8mail/utils/run.py | python | parse_args | (args) | return parser.parse_args(args) | Seperate functions to make it easier to run tests
Pass args as an array | Seperate functions to make it easier to run tests
Pass args as an array | [
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] | def parse_args(args):
"""
Seperate functions to make it easier to run tests
Pass args as an array
"""
parser = argparse.ArgumentParser(
description="Email information and password lookup tool", prog="h8mail"
)
parser.add_argument(
"-t",
"--targets",
dest="user_targets",
help="Either string inputs or files. Supports email pattern matching from input or file, filepath globing and multiple arguments",
nargs="+",
)
parser.add_argument(
"-u",
"--url",
dest="user_urls",
help="Either string inputs or files. Supports URL pattern matching from input or file, filepath globing and multiple arguments. Parse URLs page for emails. Requires http:// or https:// in URL.",
nargs="+",
)
parser.add_argument(
"-q",
"--custom-query",
dest="user_query",
help='Perform a custom query. Supports username, password, ip, hash, domain. Performs an implicit "loose" search when searching locally',
)
parser.add_argument(
"--loose",
dest="loose",
help="Allow loose search by disabling email pattern recognition. Use spaces as pattern seperators",
action="store_true",
default=False,
)
parser.add_argument(
"-c",
"--config",
dest="config_file",
help="Configuration file for API keys. Accepts keys from Snusbase, WeLeakInfo, Leak-Lookup, HaveIBeenPwned, Emailrep, Dehashed and hunterio",
nargs="+",
)
parser.add_argument(
"-o", "--output", dest="output_file", help="File to write CSV output"
)
parser.add_argument(
"-j", "--json", dest="output_json", help="File to write JSON output"
)
parser.add_argument(
"-bc",
"--breachcomp",
dest="bc_path",
help="Path to the breachcompilation torrent folder. Uses the query.sh script included in the torrent",
)
parser.add_argument(
"-sk",
"--skip-defaults",
dest="skip_defaults",
help="Skips Scylla and HunterIO check. Ideal for local scans",
action="store_true",
default=False,
)
parser.add_argument(
"-k",
"--apikey",
dest="cli_apikeys",
help='Pass config options. Supported format: "K=V,K=V"',
nargs="+",
)
parser.add_argument(
"-lb",
"--local-breach",
dest="local_breach_src",
help="Local cleartext breaches to scan for targets. Uses multiprocesses, one separate process per file, on separate worker pool by arguments. Supports file or folder as input, and filepath globing",
nargs="+",
)
parser.add_argument(
"-gz",
"--gzip",
dest="local_gzip_src",
help="Local tar.gz (gzip) compressed breaches to scans for targets. Uses multiprocesses, one separate process per file. Supports file or folder as input, and filepath globing. Looks for 'gz' in filename",
nargs="+",
)
parser.add_argument(
"-sf",
"--single-file",
dest="single_file",
help="If breach contains big cleartext or tar.gz files, set this flag to view the progress bar. Disables concurrent file searching for stability",
action="store_true",
default=False,
),
parser.add_argument(
"-ch",
"--chase",
dest="chase_limit",
help="Add related emails from hunter.io to ongoing target list. Define number of emails per target to chase. Requires hunter.io private API key if used without power-chase",
type=int,
nargs="?",
),
parser.add_argument(
"--power-chase",
dest="power_chase",
help="Add related emails from ALL API services to ongoing target list. Use with --chase",
action="store_true",
default=False,
),
parser.add_argument(
"--hide",
dest="hide",
help="Only shows the first 4 characters of found passwords to output. Ideal for demonstrations",
action="store_true",
default=False,
),
parser.add_argument(
"--debug",
dest="debug",
help="Print request debug information",
action="store_true",
default=False,
),
parser.add_argument(
"--gen-config",
"-g",
dest="gen_config",
help="Generates a configuration file template in the current working directory & exits. Will overwrite existing h8mail_config.ini file",
action="store_true",
default=False,
),
return parser.parse_args(args) | [
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CedricGuillemet/Imogen | ee417b42747ed5b46cb11b02ef0c3630000085b3 | bin/Lib/platform.py | python | mac_ver | (release='', versioninfo=('', '', ''), machine='') | return release, versioninfo, machine | Get MacOS version information and return it as tuple (release,
versioninfo, machine) with versioninfo being a tuple (version,
dev_stage, non_release_version).
Entries which cannot be determined are set to the parameter values
which default to ''. All tuple entries are strings. | Get MacOS version information and return it as tuple (release,
versioninfo, machine) with versioninfo being a tuple (version,
dev_stage, non_release_version). | [
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] | def mac_ver(release='', versioninfo=('', '', ''), machine=''):
""" Get MacOS version information and return it as tuple (release,
versioninfo, machine) with versioninfo being a tuple (version,
dev_stage, non_release_version).
Entries which cannot be determined are set to the parameter values
which default to ''. All tuple entries are strings.
"""
# First try reading the information from an XML file which should
# always be present
info = _mac_ver_xml()
if info is not None:
return info
# If that also doesn't work return the default values
return release, versioninfo, machine | [
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openstack/cinder | 23494a6d6c51451688191e1847a458f1d3cdcaa5 | cinder/api/contrib/volume_actions.py | python | VolumeActionsController._begin_detaching | (self, req, id, body) | Update volume status to 'detaching'. | Update volume status to 'detaching'. | [
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"."
] | def _begin_detaching(self, req, id, body):
"""Update volume status to 'detaching'."""
context = req.environ['cinder.context']
# Not found exception will be handled at the wsgi level
volume = self.volume_api.get(context, id)
self.volume_api.begin_detaching(context, volume) | [
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tensorflow/ranking | 94cccec8b4e71d2cc4489c61e2623522738c2924 | tensorflow_ranking/python/losses_impl.py | python | SoftmaxLoss.compute | (self, labels, logits, weights, reduction, mask=None) | return tf.compat.v1.losses.compute_weighted_loss(
losses, weights, reduction=reduction) | See `_RankingLoss`. | See `_RankingLoss`. | [
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] | def compute(self, labels, logits, weights, reduction, mask=None):
"""See `_RankingLoss`."""
logits = self.get_logits(logits)
labels, logits = self.precompute(labels, logits, weights, mask)
losses, weights = self._compute_unreduced_loss_impl(labels, logits, mask)
return tf.compat.v1.losses.compute_weighted_loss(
losses, weights, reduction=reduction) | [
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python-provy/provy | ca3d5e96a2210daf3c1fd4b96e047efff152db14 | provy/more/centos/database/mysql.py | python | MySQLRole.has_grant | (self, privileges, on, username, login_from, with_grant_option) | return False | Returns :data:`True` if the user has the specified privileges on the specified object in the given location.
:param privileges: Privileges that are being verified.
:type privileges: :class:`str`
:param on: Database object that the user holds privileges on.
:type on: :class:`str`
:param username: Name of the user to be verify.
:type username: :class:`str`
:param login_from: Locations that this user can login from. Defaults to '%' (anywhere).
:type login_from: :class:`str`
:param with_grant_option: Indicates if we are verifying against grant option.
:type with_grant_option: :class:`bool`
:return: Whether the user has the privileges or not.
:rtype: :class:`bool`
Example:
::
class MySampleRole(Role):
def provision(self):
with self.using(MySQLRole) as role:
if role.has_grant('ALL PRIVILEGES',
'database',
'user',
login_from='%',
with_grant_option=True):
pass | Returns :data:`True` if the user has the specified privileges on the specified object in the given location. | [
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] | def has_grant(self, privileges, on, username, login_from, with_grant_option):
'''
Returns :data:`True` if the user has the specified privileges on the specified object in the given location.
:param privileges: Privileges that are being verified.
:type privileges: :class:`str`
:param on: Database object that the user holds privileges on.
:type on: :class:`str`
:param username: Name of the user to be verify.
:type username: :class:`str`
:param login_from: Locations that this user can login from. Defaults to '%' (anywhere).
:type login_from: :class:`str`
:param with_grant_option: Indicates if we are verifying against grant option.
:type with_grant_option: :class:`bool`
:return: Whether the user has the privileges or not.
:rtype: :class:`bool`
Example:
::
class MySampleRole(Role):
def provision(self):
with self.using(MySQLRole) as role:
if role.has_grant('ALL PRIVILEGES',
'database',
'user',
login_from='%',
with_grant_option=True):
pass
'''
grants = self.get_user_grants(username, login_from)
grant_option_string = self._get_grant_option_string(with_grant_option)
privileges = self._get_privileges(privileges)
grant_strings = self._get_possible_grant_strings(on, username, privileges, login_from, grant_option_string)
for grant_string in grant_strings:
if grant_string in grants:
return True
return False | [
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tomplus/kubernetes_asyncio | f028cc793e3a2c519be6a52a49fb77ff0b014c9b | kubernetes_asyncio/client/models/v1_attached_volume.py | python | V1AttachedVolume.__eq__ | (self, other) | return self.to_dict() == other.to_dict() | Returns true if both objects are equal | Returns true if both objects are equal | [
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"""Returns true if both objects are equal"""
if not isinstance(other, V1AttachedVolume):
return False
return self.to_dict() == other.to_dict() | [
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privacyidea/privacyidea | 9490c12ddbf77a34ac935b082d09eb583dfafa2c | privacyidea/lib/policy.py | python | Match.user | (cls, g, scope, action, user_object) | return cls(g, name=None, scope=scope, realm=None, active=True,
resolver=None, user=None, user_object=user_object,
client=g.client_ip, action=action, adminrealm=None, time=None,
sort_by_priority=True, serial=g.serial) | Match active policies with a scope, an action and a user object (which may be None).
The client IP is matched implicitly.
:param g: context object
:param scope: the policy scope. SCOPE.ADMIN cannot be passed, ``admin``
must be used instead.
:param action: the policy action
:param user_object: the user object to match. Might also be None, which
means that the policy attributes ``user``, ``realm`` and
``resolver`` are ignored.
:type user_object: User or None
:rtype: ``Match`` | Match active policies with a scope, an action and a user object (which may be None).
The client IP is matched implicitly. | [
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"""
Match active policies with a scope, an action and a user object (which may be None).
The client IP is matched implicitly.
:param g: context object
:param scope: the policy scope. SCOPE.ADMIN cannot be passed, ``admin``
must be used instead.
:param action: the policy action
:param user_object: the user object to match. Might also be None, which
means that the policy attributes ``user``, ``realm`` and
``resolver`` are ignored.
:type user_object: User or None
:rtype: ``Match``
"""
if scope == SCOPE.ADMIN:
raise MatchingError("Match.user cannot be used for policies with scope ADMIN")
if not (user_object is None or isinstance(user_object, User)):
raise MatchingError("Invalid user")
# Username, realm and resolver will be extracted from the user_object parameter
return cls(g, name=None, scope=scope, realm=None, active=True,
resolver=None, user=None, user_object=user_object,
client=g.client_ip, action=action, adminrealm=None, time=None,
sort_by_priority=True, serial=g.serial) | [
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"("... | https://github.com/privacyidea/privacyidea/blob/9490c12ddbf77a34ac935b082d09eb583dfafa2c/privacyidea/lib/policy.py#L2727-L2750 | |
filerock/FileRock-Client | 37214f701666e76e723595f8f9ed238a42f6eb06 | filerockclient/serversession/server_session.py | python | ServerSession.connect | (self) | Make the client connect to the server. | Make the client connect to the server. | [
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"""Make the client connect to the server."""
self._input_queue.put(Command('CONNECT'), 'usercommand') | [
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kuri65536/python-for-android | 26402a08fc46b09ef94e8d7a6bbc3a54ff9d0891 | python-build/python-libs/gdata/samples/authsub/secure_authsub.py | python | HealthAuthSubHelper.GetNextUrl | (self, req) | return next_url | Computes the current URL the web app is running from.
Args:
req: mod_python mp_request instance to build the URL from.
Returns:
A string representing the web app's URL. | Computes the current URL the web app is running from. | [
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] | def GetNextUrl(self, req):
"""Computes the current URL the web app is running from.
Args:
req: mod_python mp_request instance to build the URL from.
Returns:
A string representing the web app's URL.
"""
if req.is_https():
next_url = 'https://'
else:
next_url = 'http://'
next_url += req.hostname + req.unparsed_uri
return next_url | [
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_hxb2/lib/python3.5/site-packages/redis/client.py | python | StrictRedis.pipeline | (self, transaction=True, shard_hint=None) | return StrictPipeline(
self.connection_pool,
self.response_callbacks,
transaction,
shard_hint) | Return a new pipeline object that can queue multiple commands for
later execution. ``transaction`` indicates whether all commands
should be executed atomically. Apart from making a group of operations
atomic, pipelines are useful for reducing the back-and-forth overhead
between the client and server. | Return a new pipeline object that can queue multiple commands for
later execution. ``transaction`` indicates whether all commands
should be executed atomically. Apart from making a group of operations
atomic, pipelines are useful for reducing the back-and-forth overhead
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Return a new pipeline object that can queue multiple commands for
later execution. ``transaction`` indicates whether all commands
should be executed atomically. Apart from making a group of operations
atomic, pipelines are useful for reducing the back-and-forth overhead
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"""
return StrictPipeline(
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InQuest/omnibus | 88dbf5d02f87eaa79a1cfc13d403cf854ee44c40 | omnibus-cli.py | python | Console.do_quit | (self, _) | return self._STOP_AND_EXIT | Exit Omnibus shell. | Exit Omnibus shell. | [
"Exit",
"Omnibus",
"shell",
"."
] | def do_quit(self, _):
"""Exit Omnibus shell."""
self._should_quit = True
if self.session is not None:
running('Clearing artifact cache ...')
self.session.flush()
warning('Closing Omnibus shell ...')
return self._STOP_AND_EXIT | [
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"... | https://github.com/InQuest/omnibus/blob/88dbf5d02f87eaa79a1cfc13d403cf854ee44c40/omnibus-cli.py#L119-L128 | |
cackharot/suds-py3 | 1d92cc6297efee31bfd94b50b99c431505d7de21 | suds/mx/typer.py | python | Typer.genprefix | (cls, node, ns) | Generate a prefix.
@param node: An XML node on which the prefix will be used.
@type node: L{sax.element.Element}
@param ns: A namespace needing an unique prefix.
@type ns: (prefix, uri)
@return: The I{ns} with a new prefix. | Generate a prefix. | [
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] | def genprefix(cls, node, ns):
"""
Generate a prefix.
@param node: An XML node on which the prefix will be used.
@type node: L{sax.element.Element}
@param ns: A namespace needing an unique prefix.
@type ns: (prefix, uri)
@return: The I{ns} with a new prefix.
"""
for n in range(1, 1024):
p = 'ns%d' % n
u = node.resolvePrefix(p, default=None)
if u is None or u == ns[1]:
return (p, ns[1])
raise Exception('auto prefix, exhausted') | [
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OpenCobolIDE/OpenCobolIDE | c78d0d335378e5fe0a5e74f53c19b68b55e85388 | open_cobol_ide/extlibs/pyqode/core/panels/search_and_replace.py | python | SearchAndReplacePanel._set_widget_background_color | (widget, color) | Changes the base color of a widget (background).
:param widget: widget to modify
:param color: the color to apply | Changes the base color of a widget (background).
:param widget: widget to modify
:param color: the color to apply | [
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"""
Changes the base color of a widget (background).
:param widget: widget to modify
:param color: the color to apply
"""
pal = widget.palette()
pal.setColor(pal.Base, color)
widget.setPalette(pal) | [
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buntine/SwervinMervin | e5ae51a0e4ed62783024b7e7b096398e21b6d54a | swervin_mervin/segment.py | python | Segment.should_ignore | (self, segment) | return self.top["camera"]["z"] <= s.CAMERA_DEPTH or\
self.top["screen"]["y"] <= segment.top["screen"]["y"] or\
self.bottom["screen"]["y"] >= self.top["screen"]["y"] | Returns true if this segment will be projected behind a hill, or behind us, etc. | Returns true if this segment will be projected behind a hill, or behind us, etc. | [
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"etc",
"."
] | def should_ignore(self, segment):
"""Returns true if this segment will be projected behind a hill, or behind us, etc."""
return self.top["camera"]["z"] <= s.CAMERA_DEPTH or\
self.top["screen"]["y"] <= segment.top["screen"]["y"] or\
self.bottom["screen"]["y"] >= self.top["screen"]["y"] | [
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nschaetti/EchoTorch | cba209c49e0fda73172d2e853b85c747f9f5117e | echotorch/data/datasets/MarkovChainDataset.py | python | MarkovChainDataset.__getitem__ | (self, idx) | return inputs, outputs, markov_chain | Get item
:param idx:
:return: | Get item
:param idx:
:return: | [
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"""
Get item
:param idx:
:return:
"""
# Generate a Markov chain with
# specified length
markov_chain = self._generate_markov_chain(
length=self._sample_length,
start_state=np.random.randint(low=0, high=self.n_states-1)
)
# Length of each state with morphing
state_lenght_and_morph = self._states_length + 2 * self._morphing_length
# Length of sample to get for each state
state_sample_length = self._states_length + 4 * self._morphing_length
# Empty tensor for the result
inputs = torch.zeros(self._total_length, 1)
# Outputs with each state at time t
outputs = torch.zeros(self._total_length, self.n_states)
# Save the list of samples
list_of_state_samples = list()
# For each state in the Markov chain
for state_i in range(self._sample_length):
# State
current_state = int(markov_chain[state_i].item())
# Get state dataset
state_dataset = self.states[current_state]
# Get a random sample
state_sample = state_dataset[np.random.randint(len(state_dataset))]
# State sample's length and minimum length
minimum_length = (state_sample_length + self._random_start)
# Check that the sample has
# the minimum size
if state_sample.size(0) >= minimum_length:
# Random start
if self._random_start > 0:
random_start = np.random.randint(0, self._random_start)
else:
random_start = 0
# end if
# Get a random part
state_part = state_sample[random_start:random_start+state_sample_length]
# Add to the list
list_of_state_samples.append(state_part)
else:
raise Exception("State sample length is not enough ({} vs {})!".format(state_sample_length, minimum_length))
# end if
# end for
# Go through time to compose the sample
for t in range(self._total_length):
# In which state we are
state_step = math.floor(t / state_lenght_and_morph)
last_step = state_step - 1
next_step = state_step + 1
# Bounds
state_start_time = state_step * state_lenght_and_morph
state_end_time = (state_step + 1) * state_lenght_and_morph
# Position in the state
state_position = t - state_start_time
# Are we in the morphing period
if self._morphing_length > 0:
if t - state_start_time < self._morphing_length and state_step > 0:
m = -(1.0 / (2.0 * self._morphing_length)) * state_position + 0.5
last_state_position = state_sample_length - self._morphing_length + state_position
inputs[t] = m * list_of_state_samples[last_step][last_state_position]
inputs[t] += (1.0 - m) * list_of_state_samples[state_step][state_position]
elif state_end_time - t < self._morphing_length and state_step != self._sample_length - 1:
m = (1.0 / (2.0 * self._morphing_length)) * (state_end_time - t)
next_state_position = state_sample_length - (self._morphing_length + self._states_length)
inputs[t] = m * list_of_state_samples[next_step][next_state_position]
inputs[t] += (1.0 - m) * list_of_state_samples[state_step][state_position]
else:
inputs[t] = list_of_state_samples[state_step][state_position]
# end if
else:
inputs[t] = list_of_state_samples[state_step][state_position]
# end if
# Outputs
outputs[t, int(markov_chain[state_step].item())] = 1.0
# end for
return inputs, outputs, markov_chain | [
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pyqt/examples | 843bb982917cecb2350b5f6d7f42c9b7fb142ec1 | src/pyqt-official/mainwindows/application/application.py | python | MainWindow.saveAs | (self) | return False | [] | def saveAs(self):
fileName, _ = QFileDialog.getSaveFileName(self)
if fileName:
return self.saveFile(fileName)
return False | [
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saltstack/salt | fae5bc757ad0f1716483ce7ae180b451545c2058 | salt/ext/tornado/escape.py | python | linkify | (text, shorten=False, extra_params="",
require_protocol=False, permitted_protocols=["http", "https"]) | return _URL_RE.sub(make_link, text) | Converts plain text into HTML with links.
For example: ``linkify("Hello http://tornadoweb.org!")`` would return
``Hello <a href="http://tornadoweb.org">http://tornadoweb.org</a>!``
Parameters:
* ``shorten``: Long urls will be shortened for display.
* ``extra_params``: Extra text to include in the link tag, or a callable
taking the link as an argument and returning the extra text
e.g. ``linkify(text, extra_params='rel="nofollow" class="external"')``,
or::
def extra_params_cb(url):
if url.startswith("http://example.com"):
return 'class="internal"'
else:
return 'class="external" rel="nofollow"'
linkify(text, extra_params=extra_params_cb)
* ``require_protocol``: Only linkify urls which include a protocol. If
this is False, urls such as www.facebook.com will also be linkified.
* ``permitted_protocols``: List (or set) of protocols which should be
linkified, e.g. ``linkify(text, permitted_protocols=["http", "ftp",
"mailto"])``. It is very unsafe to include protocols such as
``javascript``. | Converts plain text into HTML with links. | [
"Converts",
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"text",
"into",
"HTML",
"with",
"links",
"."
] | def linkify(text, shorten=False, extra_params="",
require_protocol=False, permitted_protocols=["http", "https"]):
"""Converts plain text into HTML with links.
For example: ``linkify("Hello http://tornadoweb.org!")`` would return
``Hello <a href="http://tornadoweb.org">http://tornadoweb.org</a>!``
Parameters:
* ``shorten``: Long urls will be shortened for display.
* ``extra_params``: Extra text to include in the link tag, or a callable
taking the link as an argument and returning the extra text
e.g. ``linkify(text, extra_params='rel="nofollow" class="external"')``,
or::
def extra_params_cb(url):
if url.startswith("http://example.com"):
return 'class="internal"'
else:
return 'class="external" rel="nofollow"'
linkify(text, extra_params=extra_params_cb)
* ``require_protocol``: Only linkify urls which include a protocol. If
this is False, urls such as www.facebook.com will also be linkified.
* ``permitted_protocols``: List (or set) of protocols which should be
linkified, e.g. ``linkify(text, permitted_protocols=["http", "ftp",
"mailto"])``. It is very unsafe to include protocols such as
``javascript``.
"""
if extra_params and not callable(extra_params):
extra_params = " " + extra_params.strip()
def make_link(m):
url = m.group(1)
proto = m.group(2)
if require_protocol and not proto:
return url # not protocol, no linkify
if proto and proto not in permitted_protocols:
return url # bad protocol, no linkify
href = m.group(1)
if not proto:
href = "http://" + href # no proto specified, use http
if callable(extra_params):
params = " " + extra_params(href).strip()
else:
params = extra_params
# clip long urls. max_len is just an approximation
max_len = 30
if shorten and len(url) > max_len:
before_clip = url
if proto:
proto_len = len(proto) + 1 + len(m.group(3) or "") # +1 for :
else:
proto_len = 0
parts = url[proto_len:].split("/")
if len(parts) > 1:
# Grab the whole host part plus the first bit of the path
# The path is usually not that interesting once shortened
# (no more slug, etc), so it really just provides a little
# extra indication of shortening.
url = url[:proto_len] + parts[0] + "/" + \
parts[1][:8].split('?')[0].split('.')[0]
if len(url) > max_len * 1.5: # still too long
url = url[:max_len]
if url != before_clip:
amp = url.rfind('&')
# avoid splitting html char entities
if amp > max_len - 5:
url = url[:amp]
url += "..."
if len(url) >= len(before_clip):
url = before_clip
else:
# full url is visible on mouse-over (for those who don't
# have a status bar, such as Safari by default)
params += ' title="%s"' % href
return u'<a href="%s"%s>%s</a>' % (href, params, url)
# First HTML-escape so that our strings are all safe.
# The regex is modified to avoid character entites other than & so
# that we won't pick up ", etc.
text = _unicode(xhtml_escape(text))
return _URL_RE.sub(make_link, text) | [
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nadineproject/nadine | c41c8ef7ffe18f1853029c97eecc329039b4af6c | nadine/management/commands/install_demo.py | python | Command.handle | (self, *args, **options) | [] | def handle(self, *args, **options):
if settings.PRODUCTION:
raise Exception('Will not install the demo on production.')
self.delete_all(BillingLog)
self.delete_all(Bill)
self.delete_all(Transaction)
self.delete_all(CoworkingDay)
self.delete_all(MembershipPlan)
self.delete_all(Membership)
self.delete_all(UserProfile)
self.delete_all(User)
self.delete_all(Industry)
self.delete_all(Neighborhood)
self.delete_all(IncomingMail)
self.delete_all(OutgoingMail)
self.delete_all(MailingList)
call_command('syncdb', interactive=False)
call_command('migrate', interactive=False)
basic_plan = MembershipPlan.objects.create(name='Basic', description='An occasional user', monthly_rate='50', daily_rate='25', dropin_allowance='5')
resident_plan = MembershipPlan.objects.create(name='Resident', description='A frequent user', monthly_rate='500', daily_rate='20', has_desk=True)
knitters_ml = MailingList.objects.create(name='Knitters', description='Knitters of the space', email_address='knitters@example.com', username='knitters', password='1234', pop_host='pop.example.com', smtp_host='smtp.example.com', )
gamers_ml = MailingList.objects.create(name='Game players', description='People who play board games', email_address='gamers@example.com', username='gamers', password='1234', pop_host='pop.example.com', smtp_host='smtp.example.com', )
alice = self.create_user('alice', '1234', 'Alice', 'Templeton', is_staff=True, is_superuser=True, email='alice@example.com')
knitters_ml.moderators.add(alice)
terry = self.create_user('terry', '1234', 'Terry', 'Moofty', email='terry@example.com')
Membership.objects.create(user=terry, membership_plan=resident_plan, start_date=timezone.now().date() - timedelta(days=400), daily_rate=0, has_desk=True)
knitters_ml.subscribers.add(terry)
bob = self.create_user('bob', '1234', 'Bob', 'Stilton', email='bob@example.com')
Membership.objects.create(user=bob, membership_plan=basic_plan, start_date=timezone.now().date() - timedelta(days=92), daily_rate=25)
knitters_ml.subscribers.add(bob) | [
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uqfoundation/mystic | 154e6302d1f2f94e8f13e88ecc5f24241cc28ac7 | mystic/scripts.py | python | _get_history | (source, ids=None) | return params, costs | get params and cost from the given source
source is the name of the trajectory logfile (or solver instance)
if provided, ids are the list of 'run ids' to select | get params and cost from the given source | [
"get",
"params",
"and",
"cost",
"from",
"the",
"given",
"source"
] | def _get_history(source, ids=None):
"""get params and cost from the given source
source is the name of the trajectory logfile (or solver instance)
if provided, ids are the list of 'run ids' to select
"""
try: # if it's a logfile, it might be multi-id
from mystic.munge import read_trajectories
step, param, cost = read_trajectories(source)
if not step: step = [(i,) for i in range(len(cost))]
except: # it's not a logfile, so read and return
from mystic.munge import read_history
param, cost = read_history(source)
return [param],[cost]
# split (i,id) into iteration and id
multinode = len(step[0]) - 1 if step else 0 #XXX: no step info, so give up
if multinode: id = [(i[1] or 0) for i in step]
else: id = [0 for i in step]
params = [[] for i in range(max(id) + 1)]
costs = [[] for i in range(len(params))]
# populate params for each id with the corresponding (param,cost)
for i in range(len(id)):
if ids is None or id[i] in ids: # take only the selected 'id'
params[id[i]].append(param[i])
costs[id[i]].append(cost[i])
params = [r for r in params if len(r)] # only keep selected 'ids'
costs = [r for r in costs if len(r)] # only keep selected 'ids'
# convert to support format
from mystic.munge import raw_to_support
for i in range(len(params)):
params[i], costs[i] = raw_to_support(params[i], costs[i])
return params, costs | [
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paulvangentcom/python_corona_simulation | a5dddd3e13d2bb768a9294d85ab27329be9a21dd | config.py | python | Configuration.set_self_isolation | (self, self_isolate_proportion=0.9,
isolation_bounds = [0.02, 0.02, 0.09, 0.98],
traveling_infects=False) | sets self-isolation scenario to active | sets self-isolation scenario to active | [
"sets",
"self",
"-",
"isolation",
"scenario",
"to",
"active"
] | def set_self_isolation(self, self_isolate_proportion=0.9,
isolation_bounds = [0.02, 0.02, 0.09, 0.98],
traveling_infects=False):
'''sets self-isolation scenario to active'''
self.self_isolate = True
self.isolation_bounds = isolation_bounds
self.self_isolate_proportion = self_isolate_proportion
#set roaming bounds to outside isolated area
self.xbounds = [0.1, 1.1]
self.ybounds = [0.02, 0.98]
#update plot bounds everything is shown
self.x_plot = [0, 1.1]
self.y_plot = [0, 1]
#update whether traveling agents also infect
self.traveling_infects = traveling_infects | [
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... | https://github.com/paulvangentcom/python_corona_simulation/blob/a5dddd3e13d2bb768a9294d85ab27329be9a21dd/config.py#L153-L168 | ||
ym2011/POC-EXP | 206b22d3a6b2a172359678df33bbc5b2ad04b6c3 | K8/Web-Exp/sqlmap/thirdparty/oset/_abc.py | python | MutableSet.clear | (self) | This is slow (creates N new iterators!) but effective. | This is slow (creates N new iterators!) but effective. | [
"This",
"is",
"slow",
"(",
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"N",
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"iterators!",
")",
"but",
"effective",
"."
] | def clear(self):
"""This is slow (creates N new iterators!) but effective."""
try:
while True:
self.pop()
except KeyError:
pass | [
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mit-han-lab/once-for-all | 4f6fce3652ee4553ea811d38f32f90ac8b1bc378 | ofa/utils/layers.py | python | ResNetBottleneckBlock.config | (self) | return {
'name': ResNetBottleneckBlock.__name__,
'in_channels': self.in_channels,
'out_channels': self.out_channels,
'kernel_size': self.kernel_size,
'stride': self.stride,
'expand_ratio': self.expand_ratio,
'mid_channels': self.mid_channels,
'act_func': self.act_func,
'groups': self.groups,
'downsample_mode': self.downsample_mode,
} | [] | def config(self):
return {
'name': ResNetBottleneckBlock.__name__,
'in_channels': self.in_channels,
'out_channels': self.out_channels,
'kernel_size': self.kernel_size,
'stride': self.stride,
'expand_ratio': self.expand_ratio,
'mid_channels': self.mid_channels,
'act_func': self.act_func,
'groups': self.groups,
'downsample_mode': self.downsample_mode,
} | [
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... | https://github.com/mit-han-lab/once-for-all/blob/4f6fce3652ee4553ea811d38f32f90ac8b1bc378/ofa/utils/layers.py#L632-L644 | |||
coala/coala | 37af7fd5de3ed148b8096cfc80e4717fb840bf2c | coalib/results/result_actions/PrintMoreInfoAction.py | python | PrintMoreInfoAction.apply | (self, result, original_file_dict, file_diff_dict) | return file_diff_dict | Print (M)ore info | Print (M)ore info | [
"Print",
"(",
"M",
")",
"ore",
"info"
] | def apply(self, result, original_file_dict, file_diff_dict):
"""
Print (M)ore info
"""
print(result.additional_info)
return file_diff_dict | [
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Source-Python-Dev-Team/Source.Python | d0ffd8ccbd1e9923c9bc44936f20613c1c76b7fb | addons/source-python/packages/site-packages/sphinx/writers/texinfo.py | python | TexinfoTranslator.collect_rellinks | (self) | Collect the relative links (next, previous, up) for each "node". | Collect the relative links (next, previous, up) for each "node". | [
"Collect",
"the",
"relative",
"links",
"(",
"next",
"previous",
"up",
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"for",
"each",
"node",
"."
] | def collect_rellinks(self):
"""Collect the relative links (next, previous, up) for each "node"."""
rellinks = self.rellinks
node_menus = self.node_menus
for id, entries in node_menus.items():
rellinks[id] = ['', '', '']
# up's
for id, entries in node_menus.items():
for e in entries:
rellinks[e][2] = id
# next's and prev's
for id, entries in node_menus.items():
for i, id in enumerate(entries):
# First child's prev is empty
if i != 0:
rellinks[id][1] = entries[i-1]
# Last child's next is empty
if i != len(entries) - 1:
rellinks[id][0] = entries[i+1]
# top's next is its first child
try:
first = node_menus['Top'][0]
except IndexError:
pass
else:
rellinks['Top'][0] = first
rellinks[first][1] = 'Top' | [
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viewfinderco/viewfinder | 453845b5d64ab5b3b826c08b02546d1ca0a07c14 | backend/www/auth_viewfinder.py | python | LoginResetViewfinderHandler._Finish | (cls, handler, client, user_dict, ident_dict, device_dict) | Invoked by VerifyViewfinderHandler to complete the login action. | Invoked by VerifyViewfinderHandler to complete the login action. | [
"Invoked",
"by",
"VerifyViewfinderHandler",
"to",
"complete",
"the",
"login",
"action",
"."
] | def _Finish(cls, handler, client, user_dict, ident_dict, device_dict):
"""Invoked by VerifyViewfinderHandler to complete the login action."""
handler._AuthUser(user_dict, ident_dict, device_dict, confirmed=True) | [
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mnemosyne-proj/mnemosyne | e39e364e56343437f2e485e0b06ca714de2f2d2e | mnemosyne/libmnemosyne/controllers/default_controller.py | python | DefaultController.create_new_cards | (self, fact_data, card_type, grade, tag_names,
check_for_duplicates=True, save=True) | return cards | Create a new set of sister cards. If the grade is 2 or higher,
we perform a initial review with that grade and move the cards into
the long term retention process. For other grades, we treat the card
as still unseen and keep its grade at -1. This puts the card on equal
footing with ungraded cards created during the import process. These
ungraded cards are pulled in at the end of the review process, either
in the order they were added, on in random order. | Create a new set of sister cards. If the grade is 2 or higher,
we perform a initial review with that grade and move the cards into
the long term retention process. For other grades, we treat the card
as still unseen and keep its grade at -1. This puts the card on equal
footing with ungraded cards created during the import process. These
ungraded cards are pulled in at the end of the review process, either
in the order they were added, on in random order. | [
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"and",
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"into",
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"long",
"term",
"retention",
"... | def create_new_cards(self, fact_data, card_type, grade, tag_names,
check_for_duplicates=True, save=True):
"""Create a new set of sister cards. If the grade is 2 or higher,
we perform a initial review with that grade and move the cards into
the long term retention process. For other grades, we treat the card
as still unseen and keep its grade at -1. This puts the card on equal
footing with ungraded cards created during the import process. These
ungraded cards are pulled in at the end of the review process, either
in the order they were added, on in random order.
"""
assert grade in [-1, 2, 3, 4, 5] # Use -1 for yet to learn cards.
assert card_type.is_fact_data_valid(fact_data)
db = self.database()
tag_names = self._retain_only_child_tags(tag_names)
tags = db.get_or_create_tags_with_names(tag_names)
fact = Fact(fact_data)
if check_for_duplicates:
duplicates = db.duplicates_for_fact(fact, card_type)
if len(duplicates) != 0:
answer = None
for duplicate in duplicates:
# Duplicates only checks equality of unique keys.
if duplicate.data == fact_data:
answer = self.main_widget().show_question(\
_("Identical card is already in database."),
_("&Do not add"), _("&Add anyway"), "")
break
if answer is None:
question = \
_("There is already data present for this card:\n\n")
existing_fact_data = {}
for fact_key in card_type.fact_keys():
existing_fact_data[fact_key] = ""
for duplicate in duplicates:
if duplicate.data == fact.data:
continue
for fact_key in fact_data:
if fact_key in duplicate.data and \
duplicate[fact_key] not in \
existing_fact_data[fact_key]:
if len(existing_fact_data[fact_key]) != 0:
existing_fact_data[fact_key] += " / "
existing_fact_data[fact_key] += \
duplicate[fact_key]
for fact_key, fact_key_name in \
card_type.fact_keys_and_names:
question += _(fact_key_name) + ": " + \
existing_fact_data[fact_key] + "\n"
answer = self.main_widget().show_question(question,
_("&Do not add"), _("&Add anyway"), _("&Merge and edit"))
if answer == 0: # Do not add.
return
if answer == 2: # Merge and edit.
db.add_fact(fact)
for duplicate in duplicates:
for card in db.cards_from_fact(duplicate):
tags.update(card.tags)
cards = card_type.create_sister_cards(fact)
for card in cards:
card.tags = tags
db.add_card(card)
if grade >= 2:
self.scheduler().set_initial_grade(cards, grade)
for card in cards:
db.update_card(card, repetition_only=True)
merged_fact_data = copy.copy(fact.data)
for duplicate in duplicates:
for fact_key in fact_data:
if fact_key in duplicate.data and \
duplicate[fact_key] not in \
merged_fact_data[fact_key]:
merged_fact_data[fact_key] += " / " \
+ duplicate[fact_key]
self.delete_facts_and_their_cards(duplicates)
card = db.cards_from_fact(fact)[0]
card.fact.data = merged_fact_data
card.tags = tags
self.component_manager.current("edit_card_dialog")\
(card, component_manager=self.component_manager,
allow_cancel=False).activate()
return db.cards_from_fact(fact)
# Create cards.
cards = card_type.create_sister_cards(fact)
db.add_fact(fact)
for card in cards:
card.tags = tags
db.add_card(card)
if grade >= 2:
self.scheduler().set_initial_grade(cards, grade)
for card in cards:
db.update_card(card, repetition_only=True)
if save:
db.save()
if self.review_controller().learning_ahead == True:
self.reset_study_mode()
return cards | [
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Qirky/FoxDot | 76318f9630bede48ff3994146ed644affa27bfa4 | FoxDot/lib/Extensions/SonicPi/__init__.py | python | GenerateSonicPiData | (sonic_pi_dir) | Generate the sonic-pi json metadata from a sonic-pi source repo | Generate the sonic-pi json metadata from a sonic-pi source repo | [
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"sonic",
"-",
"pi",
"json",
"metadata",
"from",
"a",
"sonic",
"-",
"pi",
"source",
"repo"
] | def GenerateSonicPiData(sonic_pi_dir):
""" Generate the sonic-pi json metadata from a sonic-pi source repo """
synthinfo = os.path.join(sonic_pi_dir,
'app/server/sonicpi/lib/sonicpi/synths/synthinfo')
datastr = check_output(["ruby", RUBY_SCRIPT, synthinfo])
ref = check_output(["git", "rev-parse", "HEAD"], cwd=sonic_pi_dir).strip()
data = json.loads(datastr)
data['__ref__'] = ref
with open(SONIC_PI_FILE, 'w') as ofile:
json.dump(data, ofile, separators=(',', ':')) | [
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rdehuyss/micropython-ota-updater | be4ec89994b2ac63a006113fb5cff21aa7202204 | main.py | python | connectToWifiAndUpdate | () | [] | def connectToWifiAndUpdate():
import time, machine, network, gc, app.secrets as secrets
time.sleep(1)
print('Memory free', gc.mem_free())
from app.ota_updater import OTAUpdater
sta_if = network.WLAN(network.STA_IF)
if not sta_if.isconnected():
print('connecting to network...')
sta_if.active(True)
sta_if.connect(secrets.WIFI_SSID, secrets.WIFI_PASSWORD)
while not sta_if.isconnected():
pass
print('network config:', sta_if.ifconfig())
otaUpdater = OTAUpdater('https://github.com/rdehuyss/micropython-ota-updater', main_dir='app', secrets_file="secrets.py")
hasUpdated = otaUpdater.install_update_if_available()
if hasUpdated:
machine.reset()
else:
del(otaUpdater)
gc.collect() | [
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containernet/containernet | 7b2ae38d691b2ed8da2b2700b85ed03562271d01 | examples/miniedit.py | python | customOvs.setSwitchIP | (self, ip) | Set management IP address | Set management IP address | [
"Set",
"management",
"IP",
"address"
] | def setSwitchIP(self, ip):
"Set management IP address"
self.switchIP = ip | [
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qutip/qutip | 52d01da181a21b810c3407812c670f35fdc647e8 | qutip/superop_reps.py | python | chi_to_choi | (q_oper) | return Qobj((B * q_oper * B.dag()) / q_oper.shape[0], superrep='choi') | Converts a Chi matrix to a Choi matrix.
NOTE: this is only supported for qubits right now. Need to extend to
Heisenberg-Weyl for other subsystem dimensions. | Converts a Chi matrix to a Choi matrix. | [
"Converts",
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"to",
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"."
] | def chi_to_choi(q_oper):
"""
Converts a Chi matrix to a Choi matrix.
NOTE: this is only supported for qubits right now. Need to extend to
Heisenberg-Weyl for other subsystem dimensions.
"""
nq = _nq(q_oper.dims)
B = _pauli_basis(nq)
# Force the basis change to match the dimensions of
# the input.
B.dims = q_oper.dims
# We normally should not multiply objects of different
# superreps, so Qobj warns about that. Here, however, we're actively
# converting between, so the superrep of B is irrelevant.
# To suppress warnings, we pretend that B is also a chi.
B.superrep = 'chi'
# The Chi matrix has tr(chi) == d², so we need to divide out
# by that to get back to the Choi form.
return Qobj((B * q_oper * B.dag()) / q_oper.shape[0], superrep='choi') | [
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"... | https://github.com/qutip/qutip/blob/52d01da181a21b810c3407812c670f35fdc647e8/qutip/superop_reps.py#L251-L272 | |
ntalekt/homeassistant | 8fb6da881564430a3324125ddc2bd43cb7c8680f | custom_components/monitor_docker/sensor.py | python | DockerSensor.icon | (self) | return self._var_icon | Icon to use in the frontend. | Icon to use in the frontend. | [
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"""Icon to use in the frontend."""
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KalleHallden/AutoTimer | 2d954216700c4930baa154e28dbddc34609af7ce | env/lib/python2.7/site-packages/pip/_vendor/chardet/sjisprober.py | python | SJISProber.__init__ | (self) | [] | def __init__(self):
super(SJISProber, self).__init__()
self.coding_sm = CodingStateMachine(SJIS_SM_MODEL)
self.distribution_analyzer = SJISDistributionAnalysis()
self.context_analyzer = SJISContextAnalysis()
self.reset() | [
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citronneur/rdpy | cef16a9f64d836a3221a344ca7d571644280d829 | rdpy/core/type.py | python | String.__init__ | (self, value = "", readLen = None, conditional = lambda:True, optional = False, constant = False, unicode = False, until = None) | @param value: python string use for inner value
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@param conditional : Callable object
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And optional is True, read type is ignored
@param constant: Check if object value doesn't change after read operation
@param unicode: Encode and decode value as unicode
@param until: read until sequence is readed or write sequence at the end of string | [] | def __init__(self, value = "", readLen = None, conditional = lambda:True, optional = False, constant = False, unicode = False, until = None):
"""
@param value: python string use for inner value
@param readLen: length use to read in stream (SimpleType) if 0 read entire stream
@param conditional : Callable object
Read and Write operation depend on return of this function
@param optional: If there is no enough byte in current stream
And optional is True, read type is ignored
@param constant: Check if object value doesn't change after read operation
@param unicode: Encode and decode value as unicode
@param until: read until sequence is readed or write sequence at the end of string
"""
Type.__init__(self, conditional = conditional, optional = optional, constant = constant)
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self._readLen = readLen
self._unicode = unicode
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AutodeskRoboticsLab/Mimic | 85447f0d346be66988303a6a054473d92f1ed6f4 | mimic/scripts/mimic_external_axes.py | python | get_external_axis_info | (robot_name, external_axis_name) | return info | Get's all of the external axis settings for the input external axis name
:param robot_name: string, name of robot
:param external_axis_name: string, name of external axis
:return info: dict, dictionary of input external axis setting | Get's all of the external axis settings for the input external axis name
:param robot_name: string, name of robot
:param external_axis_name: string, name of external axis
:return info: dict, dictionary of input external axis setting | [
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:param robot_name: string, name of robot
:param external_axis_name: string, name of external axis
:return info: dict, dictionary of input external axis setting
"""
info = {}
info['Robot Name'] = robot_name
info['Axis Name'] = external_axis_name
external_axis_path = _get_external_axis_path(robot_name, external_axis_name)
info['Axis Number'] = _get_external_axis_number(external_axis_path)
driving_attr_ctrl, driving_attr_name = _get_external_axis_connections(external_axis_path)
info['Driving Controller'] = driving_attr_ctrl
info['Driving Attribute'] = driving_attr_name
info['Position Limit Min'] = _get_external_axis_limits_min(external_axis_path)
info['Position Limit Max'] = _get_external_axis_limits_max(external_axis_path)
info['Velocity Limit'] = _get_external_axis_velocity_limit(external_axis_path)
info['Ignore'] = _get_external_axis_ignore(external_axis_path)
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koalalorenzo/python-digitalocean | ebea58fddf2ceea35c027bfa66f2fa9f5debfd64 | digitalocean/LoadBalancer.py | python | LoadBalancer.__str__ | (self) | return "%s" % (self.id) | [] | def __str__(self):
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Jajcus/pyxmpp2 | 59e5fd7c8837991ac265dc6aad23a6bd256768a7 | pyxmpp2/ext/muc/muccore.py | python | MucXBase.free | (self) | Unlink and free the XML node owned by `self`. | Unlink and free the XML node owned by `self`. | [
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Unlink and free the XML node owned by `self`.
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self.xmlnode=None | [
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IntelPython/sdc | 1ebf55c00ef38dfbd401a70b3945e352a5a38b87 | sdc/utilities/utils.py | python | is_assign | (inst) | return isinstance(inst, ir.Assign) | [] | def is_assign(inst):
return isinstance(inst, ir.Assign) | [
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wakatime/legacy-python-cli | 9b64548b16ab5ef16603d9a6c2620a16d0df8d46 | wakatime/packages/ntlm_auth/session_security.py | python | SessionSecurity._seal_message | (self, message) | return encrypted_message | [MS-NLMP] v28.0 2016-07-14
3.4.3 Message Confidentiality
Will generate an encrypted message using RC4 based on the ClientSealingKey
@param message: The message to be sealed (encrypted)
@return encrypted_message: The encrypted message | [MS-NLMP] v28.0 2016-07-14 | [
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"""
[MS-NLMP] v28.0 2016-07-14
3.4.3 Message Confidentiality
Will generate an encrypted message using RC4 based on the ClientSealingKey
@param message: The message to be sealed (encrypted)
@return encrypted_message: The encrypted message
"""
encrypted_message = self.outgoing_handle.update(message)
return encrypted_message | [
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Cog-Creators/Red-DiscordBot | b05933274a11fb097873ab0d1b246d37b06aa306 | redbot/core/config.py | python | Config.member_from_ids | (self, guild_id: int, member_id: int) | return self._get_base_group(self.MEMBER, str(guild_id), str(member_id)) | Returns a `Group` for the ids which represent a member.
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guild_id : int
The id of the guild of the member
member_id : int
The id of the member
Returns
-------
`Group <redbot.core.config.Group>`
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"""Returns a `Group` for the ids which represent a member.
Parameters
----------
guild_id : int
The id of the guild of the member
member_id : int
The id of the member
Returns
-------
`Group <redbot.core.config.Group>`
The member's Group object.
"""
return self._get_base_group(self.MEMBER, str(guild_id), str(member_id)) | [
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edisonlz/fastor | 342078a18363ac41d3c6b1ab29dbdd44fdb0b7b3 | base/site-packages/tencentcloud/vpc/v20170312/vpc_client.py | python | VpcClient.UnassignPrivateIpAddresses | (self, request) | 本接口（UnassignPrivateIpAddresses）用于弹性网卡退还内网 IP。
* 退还弹性网卡上的辅助内网IP，接口自动解关联弹性公网 IP。不能退还弹性网卡的主内网IP。
:param request: 调用UnassignPrivateIpAddresses所需参数的结构体。
:type request: :class:`tencentcloud.vpc.v20170312.models.UnassignPrivateIpAddressesRequest`
:rtype: :class:`tencentcloud.vpc.v20170312.models.UnassignPrivateIpAddressesResponse` | 本接口（UnassignPrivateIpAddresses）用于弹性网卡退还内网 IP。
* 退还弹性网卡上的辅助内网IP，接口自动解关联弹性公网 IP。不能退还弹性网卡的主内网IP。 | [
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] | def UnassignPrivateIpAddresses(self, request):
"""本接口（UnassignPrivateIpAddresses）用于弹性网卡退还内网 IP。
* 退还弹性网卡上的辅助内网IP，接口自动解关联弹性公网 IP。不能退还弹性网卡的主内网IP。
:param request: 调用UnassignPrivateIpAddresses所需参数的结构体。
:type request: :class:`tencentcloud.vpc.v20170312.models.UnassignPrivateIpAddressesRequest`
:rtype: :class:`tencentcloud.vpc.v20170312.models.UnassignPrivateIpAddressesResponse`
"""
try:
params = request._serialize()
body = self.call("UnassignPrivateIpAddresses", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.UnassignPrivateIpAddressesResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise e
else:
raise TencentCloudSDKException(e.message, e.message) | [
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PMEAL/OpenPNM | c9514b858d1361b2090b2f9579280cbcd476c9b0 | openpnm/topotools/_topotools.py | python | stitch_pores | (network, pores1, pores2, mode='gabriel') | r"""
Stitches together pores in a network with disconnected clusters
Parameters
----------
network : OpenPNM Network
The network to operate upon
pores1 and pores2: array_like
The pore indices of the disconnected clusters to be joined
mode : str
Dictates which tesselation method is used to identify which pores to
stitch together. Options are:
=========== =====================================================
mode meaning
=========== =====================================================
'gabriel' Uses the gabriel tesselation method
'delaunay' Uses the delaunay tesselation method
=========== =====================================================
Returns
-------
None
The network is operated on 'in-place' so nothing is returned. | r"""
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r"""
Stitches together pores in a network with disconnected clusters
Parameters
----------
network : OpenPNM Network
The network to operate upon
pores1 and pores2: array_like
The pore indices of the disconnected clusters to be joined
mode : str
Dictates which tesselation method is used to identify which pores to
stitch together. Options are:
=========== =====================================================
mode meaning
=========== =====================================================
'gabriel' Uses the gabriel tesselation method
'delaunay' Uses the delaunay tesselation method
=========== =====================================================
Returns
-------
None
The network is operated on 'in-place' so nothing is returned.
"""
from openpnm.network import Delaunay, Gabriel
pores1 = network._parse_indices(pores1)
pores2 = network._parse_indices(pores2)
C1 = network.coords[pores1, :]
C2 = network.coords[pores2, :]
crds = np.vstack((C1, C2))
if mode == 'delaunay':
net = Delaunay(points=crds, settings={'trim': False})
if mode == 'gabriel':
net = Gabriel(points=crds, settings={'trim': False})
net.set_label(pores=range(len(pores1)), label='pore.one')
net.set_label(pores=range(len(pores2)), label='pore.two')
Ts = net.find_neighbor_throats(pores=net.pores('one'), mode='xor')
conns = net.conns[Ts]
mapped_conns = np.vstack((pores1[conns[:, 0]],
pores2[conns[:, 1] - len(pores1)])).T
mapped_conns = np.sort(mapped_conns, axis=1)
extend(network=network, conns=mapped_conns, labels='stitched') | [
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pyparallel/pyparallel | 11e8c6072d48c8f13641925d17b147bf36ee0ba3 | Lib/site-packages/pip-7.1.2-py3.3.egg/pip/utils/__init__.py | python | backup_dir | (dir, ext='.bak') | return dir + extension | Figure out the name of a directory to back up the given dir to
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n = 1
extension = ext
while os.path.exists(dir + extension):
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extension = ext + str(n)
return dir + extension | [
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PowerScript/KatanaFramework | 0f6ad90a88de865d58ec26941cb4460501e75496 | lib/scapy/scapy/arch/windows/__init__.py | python | show_interfaces | (resolve_mac=True) | return ifaces.show(resolve_mac) | Print list of available network interfaces | Print list of available network interfaces | [
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CvvT/dumpDex | 92ab3b7e996194a06bf1dd5538a4954e8a5ee9c1 | python/idaapi.py | python | handle_debug_event | (*args) | return _idaapi.handle_debug_event(*args) | handle_debug_event(ev, rqflags) -> int | handle_debug_event(ev, rqflags) -> int | [
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inkandswitch/livebook | 93c8d467734787366ad084fc3566bf5cbe249c51 | public/pypyjs/modules/shutil.py | python | copystat | (src, dst) | Copy all stat info (mode bits, atime, mtime, flags) from src to dst | Copy all stat info (mode bits, atime, mtime, flags) from src to dst | [
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st = os.stat(src)
mode = stat.S_IMODE(st.st_mode)
if hasattr(os, 'utime'):
os.utime(dst, (st.st_atime, st.st_mtime))
if hasattr(os, 'chmod'):
os.chmod(dst, mode)
if hasattr(os, 'chflags') and hasattr(st, 'st_flags'):
try:
os.chflags(dst, st.st_flags)
except OSError, why:
for err in 'EOPNOTSUPP', 'ENOTSUP':
if hasattr(errno, err) and why.errno == getattr(errno, err):
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... | https://github.com/inkandswitch/livebook/blob/93c8d467734787366ad084fc3566bf5cbe249c51/public/pypyjs/modules/shutil.py#L93-L109 | ||
standardebooks/tools | f57af3c5938a9aeed9e97e82b2c130424f6033e5 | se/images.py | python | _float_to_str | (float_value: float) | return "{0:.2f}".format(round(float_value, 2)) | [] | def _float_to_str(float_value: float) -> str:
return "{0:.2f}".format(round(float_value, 2)) | [
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cvjena/semantic-embeddings | 0d4177422bafbba685fb6a0f976675864f31e09f | utils.py | python | l2norm | (x) | return K.tf.nn.l2_normalize(x, -1) | L2-normalizes a tensor along the last axis. | L2-normalizes a tensor along the last axis. | [
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""" L2-normalizes a tensor along the last axis. """
return K.tf.nn.l2_normalize(x, -1) | [
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hyperspy/hyperspy | 1ffb3fab33e607045a37f30c1463350b72617e10 | hyperspy/io_plugins/sur.py | python | DigitalSurfHandler._build_general_1D_data | (self,) | Build general 1D Data objects. Currently work with spectra | Build general 1D Data objects. Currently work with spectra | [
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] | def _build_general_1D_data(self,):
"""Build general 1D Data objects. Currently work with spectra"""
#Check that the object contained only one object.
#Probably overkill at this point but better safe than sorry
if len(self._list_sur_file_content) != 1:
raise MountainsMapFileError("Corrupt file")
#We get the dictionary with all the data
hypdic = self._list_sur_file_content[0]
#Add the axe to the signal dict
self.signal_dict['axes'].append(\
self._build_Xax(hypdic,ind=0,nav=False))
#We reshape the data in the correct format
self.signal_dict['data'] = hypdic['_62_points']
#Build the metadata
self._set_metadata_and_original_metadata(hypdic) | [
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tp4a/teleport | 1fafd34f1f775d2cf80ea4af6e44468d8e0b24ad | server/www/packages/packages-darwin/x64/tornado/auth.py | python | GoogleOAuth2Mixin._on_access_token | (self, future, response_fut) | Callback function for the exchange to the access token. | Callback function for the exchange to the access token. | [
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] | def _on_access_token(self, future, response_fut):
"""Callback function for the exchange to the access token."""
try:
response = response_fut.result()
except Exception as e:
future.set_exception(AuthError('Google auth error: %s' % str(e)))
return
args = escape.json_decode(response.body)
future_set_result_unless_cancelled(future, args) | [
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citronneur/rdpy | cef16a9f64d836a3221a344ca7d571644280d829 | rdpy/protocol/rdp/rdp.py | python | RDPClientObserver.__init__ | (self, controller) | @param controller: RDP controller use to interact with protocol | [] | def __init__(self, controller):
"""
@param controller: RDP controller use to interact with protocol
"""
self._controller = controller
self._controller.addClientObserver(self) | [
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dimagi/commcare-hq | d67ff1d3b4c51fa050c19e60c3253a79d3452a39 | corehq/apps/app_manager/suite_xml/post_process/remote_requests.py | python | RemoteRequestFactory.get_smart_link_function | (self) | return f"concat('{prefix}', $domain, '{suffix}'{params})" | [] | def get_smart_link_function(self):
# Returns XPath that will evaluate to a URL.
# For example, return value could be
# concat('https://www.cchq.org/a/', $domain, '/app/v1/123/smartlink/', '?arg1=', $arg1, '&arg2=', $arg2)
# Which could evaluate to
# https://www.cchq.org/a/mydomain/app/v1/123/smartlink/?arg1=abd&arg2=def
app_id = self.app.upstream_app_id if is_linked_app(self.app) else self.app.origin_id
url = absolute_reverse("session_endpoint", args=["---", app_id, self.module.session_endpoint_id])
prefix, suffix = url.split("---")
params = ""
argument_ids = self.endpoint_argument_ids
if argument_ids:
params = f", '?{argument_ids[-1]}=', ${argument_ids[-1]}"
for argument_id in argument_ids[:-1]:
params += f", '&{argument_id}=', ${argument_id}"
return f"concat('{prefix}', $domain, '{suffix}'{params})" | [
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"# https:/... | https://github.com/dimagi/commcare-hq/blob/d67ff1d3b4c51fa050c19e60c3253a79d3452a39/corehq/apps/app_manager/suite_xml/post_process/remote_requests.py#L298-L313 | |||
celery/django-celery-beat | fa73034be892052893e4ef17926ef3a5d4a21ea2 | django_celery_beat/utils.py | python | is_database_scheduler | (scheduler) | return (
scheduler == 'django'
or issubclass(symbol_by_name(scheduler), DatabaseScheduler)
) | Return true if Celery is configured to use the db scheduler. | Return true if Celery is configured to use the db scheduler. | [
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] | def is_database_scheduler(scheduler):
"""Return true if Celery is configured to use the db scheduler."""
if not scheduler:
return False
from kombu.utils import symbol_by_name
from .schedulers import DatabaseScheduler
return (
scheduler == 'django'
or issubclass(symbol_by_name(scheduler), DatabaseScheduler)
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out0fmemory/GoAgent-Always-Available | c4254984fea633ce3d1893fe5901debd9f22c2a9 | server/lib/google/appengine/ext/ndb/model.py | python | Model._get_property_for | (self, p, indexed=True, depth=0) | return prop | Internal helper to get the Property for a protobuf-level property. | Internal helper to get the Property for a protobuf-level property. | [
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] | def _get_property_for(self, p, indexed=True, depth=0):
"""Internal helper to get the Property for a protobuf-level property."""
parts = p.name().split('.')
if len(parts) <= depth:
# Apparently there's an unstructured value here.
# Assume it is a None written for a missing value.
# (It could also be that a schema change turned an unstructured
# value into a structured one. In that case, too, it seems
# better to return None than to return an unstructured value,
# since the latter doesn't match the current schema.)
return None
next = parts[depth]
prop = self._properties.get(next)
if prop is None:
prop = self._fake_property(p, next, indexed)
return prop | [
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Source-Python-Dev-Team/Source.Python | d0ffd8ccbd1e9923c9bc44936f20613c1c76b7fb | addons/source-python/packages/site-packages/pygments/formatter.py | python | Formatter.get_style_defs | (self, arg='') | return '' | Return the style definitions for the current style as a string.
``arg`` is an additional argument whose meaning depends on the
formatter used. Note that ``arg`` can also be a list or tuple
for some formatters like the html formatter. | Return the style definitions for the current style as a string. | [
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"""
Return the style definitions for the current style as a string.
``arg`` is an additional argument whose meaning depends on the
formatter used. Note that ``arg`` can also be a list or tuple
for some formatters like the html formatter.
"""
return '' | [
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reingart/pyfpdf | cb3340806c140b6e63eb4ce9d6230be84fba456e | fpdf/fpdf.py | python | FPDF.get_y | (self) | return self.y | Get y position | Get y position | [
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"Get y position"
return self.y | [
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zbarge/stocklook | d40bf60566681acd1e970818450228602bb7d8a5 | stocklook/crypto/gdax/order_mm.py | python | GdaxMMOrder.op_order | (self) | return self._op_order | Applies only to sell orders. Returns the opposite side
of the trade. Used to calculate stop-outs and profit/loss.
:return: | Applies only to sell orders. Returns the opposite side
of the trade. Used to calculate stop-outs and profit/loss.
:return: | [
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"""
Applies only to sell orders. Returns the opposite side
of the trade. Used to calculate stop-outs and profit/loss.
:return:
"""
return self._op_order | [
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carla-simulator/scenario_runner | f4d00d88eda4212a1e119515c96281a4be5c234e | srunner/scenariomanager/weather_sim.py | python | Weather.update | (self, delta_time=0) | If the weather animation is true, the new sun position is calculated w.r.t delta_time
Nothing happens if animation or datetime are None.
Args:
delta_time (float): Time passed since self.datetime [seconds]. | If the weather animation is true, the new sun position is calculated w.r.t delta_time | [
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] | def update(self, delta_time=0):
"""
If the weather animation is true, the new sun position is calculated w.r.t delta_time
Nothing happens if animation or datetime are None.
Args:
delta_time (float): Time passed since self.datetime [seconds].
"""
if not self.animation or not self.datetime:
return
self.datetime = self.datetime + datetime.timedelta(seconds=delta_time)
self._observer_location.date = self.datetime
self._sun.compute(self._observer_location)
self.carla_weather.sun_altitude_angle = math.degrees(self._sun.alt)
self.carla_weather.sun_azimuth_angle = math.degrees(self._sun.az) | [
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wistbean/fxxkpython | 88e16d79d8dd37236ba6ecd0d0ff11d63143968c | vip/qyxuan/projects/venv/lib/python3.6/site-packages/pip-19.0.3-py3.6.egg/pip/_vendor/urllib3/util/ssl_.py | python | assert_fingerprint | (cert, fingerprint) | Checks if given fingerprint matches the supplied certificate.
:param cert:
Certificate as bytes object.
:param fingerprint:
Fingerprint as string of hexdigits, can be interspersed by colons. | Checks if given fingerprint matches the supplied certificate. | [
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] | def assert_fingerprint(cert, fingerprint):
"""
Checks if given fingerprint matches the supplied certificate.
:param cert:
Certificate as bytes object.
:param fingerprint:
Fingerprint as string of hexdigits, can be interspersed by colons.
"""
fingerprint = fingerprint.replace(':', '').lower()
digest_length = len(fingerprint)
hashfunc = HASHFUNC_MAP.get(digest_length)
if not hashfunc:
raise SSLError(
'Fingerprint of invalid length: {0}'.format(fingerprint))
# We need encode() here for py32; works on py2 and p33.
fingerprint_bytes = unhexlify(fingerprint.encode())
cert_digest = hashfunc(cert).digest()
if not _const_compare_digest(cert_digest, fingerprint_bytes):
raise SSLError('Fingerprints did not match. Expected "{0}", got "{1}".'
.format(fingerprint, hexlify(cert_digest))) | [
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jgagneastro/coffeegrindsize | 22661ebd21831dba4cf32bfc6ba59fe3d49f879c | App/dist/coffeegrindsize.app/Contents/Resources/lib/python3.7/pandas/core/arrays/base.py | python | ExtensionArray.dropna | (self) | return self[~self.isna()] | Return ExtensionArray without NA values
Returns
-------
valid : ExtensionArray | Return ExtensionArray without NA values | [
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] | def dropna(self):
"""
Return ExtensionArray without NA values
Returns
-------
valid : ExtensionArray
"""
return self[~self.isna()] | [
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magenta/magenta | be6558f1a06984faff6d6949234f5fe9ad0ffdb5 | magenta/models/rl_tuner/note_rnn_loader.py | python | NoteRNNLoader.build_graph | (self) | Constructs the portion of the graph that belongs to this model. | Constructs the portion of the graph that belongs to this model. | [
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] | def build_graph(self):
"""Constructs the portion of the graph that belongs to this model."""
tf.logging.info('Initializing melody RNN graph for scope %s', self.scope)
with self.graph.as_default():
with tf.device(lambda op: ''):
with tf.variable_scope(self.scope):
# Make an LSTM cell with the number and size of layers specified in
# hparams.
if self.note_rnn_type == 'basic_rnn':
self.cell = events_rnn_graph.make_rnn_cell(
self.hparams.rnn_layer_sizes)
else:
self.cell = rl_tuner_ops.make_rnn_cell(self.hparams.rnn_layer_sizes)
# Shape of melody_sequence is batch size, melody length, number of
# output note actions.
self.melody_sequence = tf.placeholder(tf.float32,
[None, None,
self.hparams.one_hot_length],
name='melody_sequence')
self.lengths = tf.placeholder(tf.int32, [None], name='lengths')
self.initial_state = tf.placeholder(tf.float32,
[None, self.cell.state_size],
name='initial_state')
if self.training_file_list is not None:
# Set up a tf queue to read melodies from the training data tfrecord
(self.train_sequence,
self.train_labels,
self.train_lengths) = sequence_example_lib.get_padded_batch(
self.training_file_list, self.hparams.batch_size,
self.hparams.one_hot_length)
# Closure function is used so that this part of the graph can be
# re-run in multiple places, such as __call__.
def run_network_on_melody(m_seq,
lens,
initial_state,
swap_memory=True,
parallel_iterations=1):
"""Internal function that defines the RNN network structure.
Args:
m_seq: A batch of melody sequences of one-hot notes.
lens: Lengths of the melody_sequences.
initial_state: Vector representing the initial state of the RNN.
swap_memory: Uses more memory and is faster.
parallel_iterations: Argument to tf.nn.dynamic_rnn.
Returns:
Output of network (either softmax or logits) and RNN state.
"""
outputs, final_state = tf.nn.dynamic_rnn(
self.cell,
m_seq,
sequence_length=lens,
initial_state=initial_state,
swap_memory=swap_memory,
parallel_iterations=parallel_iterations)
outputs_flat = tf.reshape(outputs,
[-1, self.hparams.rnn_layer_sizes[-1]])
if self.note_rnn_type == 'basic_rnn':
linear_layer = tf_slim.layers.linear
else:
linear_layer = tf_slim.layers.legacy_linear
logits_flat = linear_layer(
outputs_flat, self.hparams.one_hot_length)
return logits_flat, final_state
(self.logits, self.state_tensor) = run_network_on_melody(
self.melody_sequence, self.lengths, self.initial_state)
self.softmax = tf.nn.softmax(self.logits)
self.run_network_on_melody = run_network_on_melody
if self.training_file_list is not None:
# Does not recreate the model architecture but rather uses it to feed
# data from the training queue through the model.
with tf.variable_scope(self.scope, reuse=True):
zero_state = self.cell.zero_state(
batch_size=self.hparams.batch_size, dtype=tf.float32)
(self.train_logits, self.train_state) = run_network_on_melody(
self.train_sequence, self.train_lengths, zero_state)
self.train_softmax = tf.nn.softmax(self.train_logits) | [
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"(",
")",
":",
"with",
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".",
"device"... | https://github.com/magenta/magenta/blob/be6558f1a06984faff6d6949234f5fe9ad0ffdb5/magenta/models/rl_tuner/note_rnn_loader.py#L175-L260 | ||
hatRiot/zarp | 2e772350a01c2aeed3f4da9685cd0cc5d6b3ecad | src/lib/scapy/fields.py | python | Emph.__eq__ | (self, other) | return self.fld == other | [] | def __eq__(self, other):
return self.fld == other | [
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] | https://github.com/hatRiot/zarp/blob/2e772350a01c2aeed3f4da9685cd0cc5d6b3ecad/src/lib/scapy/fields.py#L108-L109 | |||
hubblestack/hubble | 763142474edcecdec5fd25591dc29c3536e8f969 | hubblestack/modules/mount.py | python | remount | (name, device, mkmnt=False, fstype="", opts="defaults", user=None) | return mount(name, device, mkmnt, fstype, opts, user=user) | Attempt to remount a device, if the device is not already mounted, mount
is called
CLI Example:
.. code-block:: bash
salt '*' mount.remount /mnt/foo /dev/sdz1 True | Attempt to remount a device, if the device is not already mounted, mount
is called | [
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] | def remount(name, device, mkmnt=False, fstype="", opts="defaults", user=None):
"""
Attempt to remount a device, if the device is not already mounted, mount
is called
CLI Example:
.. code-block:: bash
salt '*' mount.remount /mnt/foo /dev/sdz1 True
"""
force_mount = False
if __grains__["os"] in ["MacOS", "Darwin"]:
if opts == "defaults":
opts = "noowners"
if fstype == "smbfs":
force_mount = True
if "AIX" in __grains__["os"]:
if opts == "defaults":
opts = []
if isinstance(opts, str):
opts = opts.split(",")
mnts = active()
if name in mnts:
# The mount point is mounted, attempt to remount it with the given data
if "remount" not in opts and __grains__["os"] not in [
"OpenBSD",
"MacOS",
"Darwin",
]:
opts.append("remount")
if force_mount:
# We need to force the mount but first we should unmount
umount(name, device, user=user)
lopts = ",".join(opts)
args = "-o {0}".format(lopts)
if fstype:
# use of fstype on AIX differs from typical Linux use of
# -t functionality AIX uses -v vfsname, -t fstype mounts
# all with fstype in /etc/filesystems
if "AIX" in __grains__["os"]:
args += " -v {0}".format(fstype)
elif "solaris" in __grains__["os"].lower():
args += " -F {0}".format(fstype)
else:
args += " -t {0}".format(fstype)
if __grains__["os"] not in ["OpenBSD", "MacOS", "Darwin"] or force_mount:
cmd = "mount {0} {1} {2} ".format(args, device, name)
else:
cmd = "mount -u {0} {1} {2} ".format(args, device, name)
out = __mods__["cmd.run_all"](cmd, runas=user, python_shell=False)
if out["retcode"]:
return out["stderr"]
return True
# Mount a filesystem that isn't already
return mount(name, device, mkmnt, fstype, opts, user=user) | [
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gramps-project/gramps | 04d4651a43eb210192f40a9f8c2bad8ee8fa3753 | gramps/plugins/lib/libgedcom.py | python | GedcomParser.__event_note | (self, line, state) | @param line: The current line in GedLine format
@type line: GedLine
@param state: The current state
@type state: CurrentState | [] | def __event_note(self, line, state):
"""
@param line: The current line in GedLine format
@type line: GedLine
@param state: The current state
@type state: CurrentState
"""
self.__parse_note(line, state.event, state) | [
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deluge-torrent/deluge | 2316088f5c0dd6cb044d9d4832fa7d56dcc79cdc | deluge/ui/gtk3/mainwindow.py | python | MainWindow.quit | (self, shutdown=False, restart=False) | Quits the GtkUI application.
Args:
shutdown (bool): Whether or not to shutdown the daemon as well.
restart (bool): Whether or not to restart the application after closing. | Quits the GtkUI application. | [
"Quits",
"the",
"GtkUI",
"application",
"."
] | def quit(self, shutdown=False, restart=False): # noqa: A003 python builtin
"""Quits the GtkUI application.
Args:
shutdown (bool): Whether or not to shutdown the daemon as well.
restart (bool): Whether or not to restart the application after closing.
"""
def quit_gtkui():
def stop_gtk_reactor(result=None):
self.restart = restart
try:
reactor.callLater(0, reactor.fireSystemEvent, 'gtkui_close')
except ReactorNotRunning:
log.debug('Attempted to stop the reactor but it is not running...')
if shutdown:
client.daemon.shutdown().addCallback(stop_gtk_reactor)
elif not client.is_standalone() and client.connected():
client.disconnect().addCallback(stop_gtk_reactor)
else:
stop_gtk_reactor()
if self.config['lock_tray'] and not self.visible():
dialog = PasswordDialog(_('Enter your password to Quit Deluge...'))
def on_dialog_response(response_id):
if response_id == Gtk.ResponseType.OK:
if (
self.config['tray_password']
== sha(decode_bytes(dialog.get_password()).encode()).hexdigest()
):
quit_gtkui()
dialog.run().addCallback(on_dialog_response)
else:
quit_gtkui() | [
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... | https://github.com/deluge-torrent/deluge/blob/2316088f5c0dd6cb044d9d4832fa7d56dcc79cdc/deluge/ui/gtk3/mainwindow.py#L228-L265 | ||
TurboGears/tg2 | f40a82d016d70ce560002593b4bb8f83b57f87b3 | tg/util/decorators.py | python | no_warn | (f, *args, **kwargs) | return update_wrapper(_f, f) | Decorator that suppresses warnings inside the decorated function | Decorator that suppresses warnings inside the decorated function | [
"Decorator",
"that",
"suppresses",
"warnings",
"inside",
"the",
"decorated",
"function"
] | def no_warn(f, *args, **kwargs):
"""Decorator that suppresses warnings inside the decorated function"""
def _f(*args, **kwargs):
warnings.simplefilter("ignore")
f(*args, **kwargs)
warnings.resetwarnings()
return update_wrapper(_f, f) | [
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... | https://github.com/TurboGears/tg2/blob/f40a82d016d70ce560002593b4bb8f83b57f87b3/tg/util/decorators.py#L5-L11 | |
numba/llvmlite | aeddf447d4befc336b26bde8c46042553a13cf75 | llvmlite/binding/executionengine.py | python | create_mcjit_compiler | (module, target_machine) | return ExecutionEngine(engine, module=module) | Create a MCJIT ExecutionEngine from the given *module* and
*target_machine*. | Create a MCJIT ExecutionEngine from the given *module* and
*target_machine*. | [
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"."
] | def create_mcjit_compiler(module, target_machine):
"""
Create a MCJIT ExecutionEngine from the given *module* and
*target_machine*.
"""
with ffi.OutputString() as outerr:
engine = ffi.lib.LLVMPY_CreateMCJITCompiler(
module, target_machine, outerr)
if not engine:
raise RuntimeError(str(outerr))
target_machine._owned = True
return ExecutionEngine(engine, module=module) | [
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... | https://github.com/numba/llvmlite/blob/aeddf447d4befc336b26bde8c46042553a13cf75/llvmlite/binding/executionengine.py#L12-L24 | |
openshift/openshift-tools | 1188778e728a6e4781acf728123e5b356380fe6f | openshift/installer/vendored/openshift-ansible-3.11.28-1/roles/lib_openshift/library/oc_process.py | python | OpenShiftCLI._replace | (self, fname, force=False) | return self.openshift_cmd(cmd) | replace the current object with oc replace | replace the current object with oc replace | [
"replace",
"the",
"current",
"object",
"with",
"oc",
"replace"
] | def _replace(self, fname, force=False):
'''replace the current object with oc replace'''
# We are removing the 'resourceVersion' to handle
# a race condition when modifying oc objects
yed = Yedit(fname)
results = yed.delete('metadata.resourceVersion')
if results[0]:
yed.write()
cmd = ['replace', '-f', fname]
if force:
cmd.append('--force')
return self.openshift_cmd(cmd) | [
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saghul/evergreen | 22f22f45892f397c23c3e09e6ea1ad4c00b3add8 | evergreen/locks.py | python | Barrier.n_waiting | (self) | return 0 | Return the number of threads currently waiting at the barrier. | Return the number of threads currently waiting at the barrier. | [
"Return",
"the",
"number",
"of",
"threads",
"currently",
"waiting",
"at",
"the",
"barrier",
"."
] | def n_waiting(self):
"""Return the number of threads currently waiting at the barrier."""
# We don't need synchronization here since this is an ephemeral result
# anyway. It returns the correct value in the steady state.
if self._state == 0:
return self._count
return 0 | [
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] | https://github.com/saghul/evergreen/blob/22f22f45892f397c23c3e09e6ea1ad4c00b3add8/evergreen/locks.py#L366-L372 | |
jupyter/kernel_gateway | 440fef1cd29c829e2141bb4c76ed5f9572b428e1 | kernel_gateway/services/kernels/pool.py | python | ManagedKernelPool.release | (self, kernel_id) | Puts a kernel back into the pool of kernels available to handle
requests.
Parameters
----------
kernel_id : str
Kernel to return to the pool | Puts a kernel back into the pool of kernels available to handle
requests. | [
"Puts",
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"kernel",
"back",
"into",
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"pool",
"of",
"kernels",
"available",
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"."
] | def release(self, kernel_id):
"""Puts a kernel back into the pool of kernels available to handle
requests.
Parameters
----------
kernel_id : str
Kernel to return to the pool
"""
self.kernel_pool.append(kernel_id)
self.kernel_semaphore.release() | [
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")"
] | https://github.com/jupyter/kernel_gateway/blob/440fef1cd29c829e2141bb4c76ed5f9572b428e1/kernel_gateway/services/kernels/pool.py#L100-L110 | ||
python/cpython | e13cdca0f5224ec4e23bdd04bb3120506964bc8b | Lib/idlelib/colorizer.py | python | ColorDelegator.recolorize_main | (self) | Evaluate text and apply colorizing tags. | Evaluate text and apply colorizing tags. | [
"Evaluate",
"text",
"and",
"apply",
"colorizing",
"tags",
"."
] | def recolorize_main(self):
"Evaluate text and apply colorizing tags."
next = "1.0"
while todo_tag_range := self.tag_nextrange("TODO", next):
self.tag_remove("SYNC", todo_tag_range[0], todo_tag_range[1])
sync_tag_range = self.tag_prevrange("SYNC", todo_tag_range[0])
head = sync_tag_range[1] if sync_tag_range else "1.0"
chars = ""
next = head
lines_to_get = 1
ok = False
while not ok:
mark = next
next = self.index(mark + "+%d lines linestart" %
lines_to_get)
lines_to_get = min(lines_to_get * 2, 100)
ok = "SYNC" in self.tag_names(next + "-1c")
line = self.get(mark, next)
##print head, "get", mark, next, "->", repr(line)
if not line:
return
for tag in self.tagdefs:
self.tag_remove(tag, mark, next)
chars += line
self._add_tags_in_section(chars, head)
if "SYNC" in self.tag_names(next + "-1c"):
head = next
chars = ""
else:
ok = False
if not ok:
# We're in an inconsistent state, and the call to
# update may tell us to stop. It may also change
# the correct value for "next" (since this is a
# line.col string, not a true mark). So leave a
# crumb telling the next invocation to resume here
# in case update tells us to leave.
self.tag_add("TODO", next)
self.update()
if self.stop_colorizing:
if DEBUG: print("colorizing stopped")
return | [
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PowerScript/KatanaFramework | 0f6ad90a88de865d58ec26941cb4460501e75496 | lib/scapy/scapy/contrib/gsm_um.py | python | partialRelease | () | return packet | PARTIAL RELEASE Section 9.1.26 | PARTIAL RELEASE Section 9.1.26 | [
"PARTIAL",
"RELEASE",
"Section",
"9",
".",
"1",
".",
"26"
] | def partialRelease():
"""PARTIAL RELEASE Section 9.1.26"""
a = TpPd(pd=0x6)
b = MessageType(mesType=0xa) # 00001010
c = ChannelDescription()
packet = a / b / c
return packet | [
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sfepy/sfepy | 02ec7bb2ab39ee1dfe1eb4cd509f0ffb7dcc8b25 | examples/diffusion/laplace_iga_interactive.py | python | create_patch | (R1, R2, C1, C2, order=2, viewpatch=False) | Create a single 2d NURBS-patch of the area between two coplanar nested
circles using igakit.
Parameters
----------
R1 : float
Radius of the inner circle.
R2 : float
Radius of the outer circle.
C1 : list of two floats
Coordinates of the center of the inner circle given as [x1, y1].
C2 : list of two floats
Coordinates of the center of the outer circle given as [x2, y2].
order : int, optional
Degree of the NURBS basis functions. The default is 2.
viewpatch : bool, optional
When set to True, display the NURBS patch. The default is False.
Returns
-------
None. | Create a single 2d NURBS-patch of the area between two coplanar nested
circles using igakit. | [
"Create",
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"of",
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"area",
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"two",
"coplanar",
"nested",
"circles",
"using",
"igakit",
"."
] | def create_patch(R1, R2, C1, C2, order=2, viewpatch=False):
"""
Create a single 2d NURBS-patch of the area between two coplanar nested
circles using igakit.
Parameters
----------
R1 : float
Radius of the inner circle.
R2 : float
Radius of the outer circle.
C1 : list of two floats
Coordinates of the center of the inner circle given as [x1, y1].
C2 : list of two floats
Coordinates of the center of the outer circle given as [x2, y2].
order : int, optional
Degree of the NURBS basis functions. The default is 2.
viewpatch : bool, optional
When set to True, display the NURBS patch. The default is False.
Returns
-------
None.
"""
from sfepy.discrete.iga.domain_generators import create_from_igakit
import sfepy.discrete.iga.io as io
from igakit.cad import circle, ruled
from igakit.plot import plt as iplt
from numpy import pi
# Assert the inner circle is inside the outer one
inter_centers = nm.sqrt((C2[0]-C1[0])**2 + (C2[1]-C1[1])**2)
assert R2>R1, "Outer circle should have a larger radius than the inner one"
assert inter_centers<R2-R1, "Circles are not nested"
# Geometry Creation
centers_direction = [C2[0]-C1[0], C2[1]-C1[1]]
if centers_direction[0]==0 and centers_direction[1]==0:
start_angle = 0.0
else:
start_angle = nm.arctan2(centers_direction[1], centers_direction[0])
c1 = circle(radius=R1, center=C1, angle=(start_angle, start_angle + 2*pi))
c2 = circle(radius=R2, center=C2, angle=(start_angle, start_angle + 2*pi))
srf = ruled(c1,c2).transpose() # make the radial direction first
# Refinement
insert_U = insert_uniformly(srf.knots[0], 6)
insert_V = insert_uniformly(srf.knots[1], 6)
srf.refine(0, insert_U).refine(1, insert_V)
# Setting the NURBS-surface degree
srf.elevate(0, order-srf.degree[0] if order-srf.degree[0] > 0 else 0)
srf.elevate(1, order-srf.degree[1] if order-srf.degree[1] > 0 else 0)
# Sfepy .iga file creation
nurbs, bmesh, regions = create_from_igakit(srf, verbose=True)
# Save .iga file in sfepy/meshes/iga
filename_domain = data_dir + '/meshes/iga/concentric_circles.iga'
io.write_iga_data(filename_domain, None, nurbs.knots, nurbs.degrees,
nurbs.cps, nurbs.weights, nurbs.cs, nurbs.conn,
bmesh.cps, bmesh.weights, bmesh.conn, regions)
if viewpatch:
try:
iplt.use('mayavi')
iplt.figure()
iplt.plot(srf)
iplt.show()
except ImportError:
iplt.use('matplotlib')
iplt.figure()
iplt.plot(srf)
iplt.show() | [
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