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FederatedAI/FATE
|
32540492623568ecd1afcb367360133616e02fa3
|
python/federatedml/secureprotol/spdz/utils/random_utils.py
|
python
|
_MixRand._inc
|
(self)
|
[] |
def _inc(self):
self._caches.append(random.SystemRandom().randint(self._lower, self._upper))
|
[
"def",
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] |
https://github.com/FederatedAI/FATE/blob/32540492623568ecd1afcb367360133616e02fa3/python/federatedml/secureprotol/spdz/utils/random_utils.py#L54-L55
|
||||
openatx/facebook-wda
|
0b01d58cfc4a1971896fc116885e27baf9ffcaf1
|
wda/__init__.py
|
python
|
Alert.click_exists
|
(self, buttons: Optional[Union[str, list]] = None)
|
Args:
- buttons: the name of the button of list of names
Returns:
button_name clicked or None
|
Args:
- buttons: the name of the button of list of names
|
[
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"names"
] |
def click_exists(self, buttons: Optional[Union[str, list]] = None):
"""
Args:
- buttons: the name of the button of list of names
Returns:
button_name clicked or None
"""
try:
return self.click(buttons)
except (ValueError, WDARequestError):
return None
|
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https://github.com/openatx/facebook-wda/blob/0b01d58cfc4a1971896fc116885e27baf9ffcaf1/wda/__init__.py#L1211-L1222
|
||
mautrix/telegram
|
9f48eca5a6654bc38012cb761ecaaaf416aabdd0
|
mautrix_telegram/commands/telegram/misc.py
|
python
|
sync
|
(evt: CommandEvent)
|
return await evt.reply("Synchronization complete.")
|
[] |
async def sync(evt: CommandEvent) -> EventID:
if len(evt.args) > 0:
sync_only = evt.args[0]
if sync_only not in ("chats", "contacts", "me"):
return await evt.reply("**Usage:** `$cmdprefix+sp sync [chats|contacts|me]`")
else:
sync_only = None
if not sync_only or sync_only == "chats":
await evt.reply("Synchronizing chats...")
await evt.sender.sync_dialogs()
if not sync_only or sync_only == "contacts":
await evt.reply("Synchronizing contacts...")
await evt.sender.sync_contacts()
if not sync_only or sync_only == "me":
await evt.sender.update_info()
return await evt.reply("Synchronization complete.")
|
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] |
https://github.com/mautrix/telegram/blob/9f48eca5a6654bc38012cb761ecaaaf416aabdd0/mautrix_telegram/commands/telegram/misc.py#L239-L255
|
|||
andresriancho/w3af
|
cd22e5252243a87aaa6d0ddea47cf58dacfe00a9
|
w3af/plugins/attack/db/sqlmap/plugins/dbms/sqlite/syntax.py
|
python
|
Syntax.__init__
|
(self)
|
[] |
def __init__(self):
GenericSyntax.__init__(self)
|
[
"def",
"__init__",
"(",
"self",
")",
":",
"GenericSyntax",
".",
"__init__",
"(",
"self",
")"
] |
https://github.com/andresriancho/w3af/blob/cd22e5252243a87aaa6d0ddea47cf58dacfe00a9/w3af/plugins/attack/db/sqlmap/plugins/dbms/sqlite/syntax.py#L15-L16
|
||||
MichaelGrupp/evo
|
c65af3b69188aaadbbd7b5f99ac7973d74343d65
|
evo/core/trajectory.py
|
python
|
PoseTrajectory3D.get_infos
|
(self)
|
return infos
|
:return: dictionary with some infos about the trajectory
|
:return: dictionary with some infos about the trajectory
|
[
":",
"return",
":",
"dictionary",
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"infos",
"about",
"the",
"trajectory"
] |
def get_infos(self) -> dict:
"""
:return: dictionary with some infos about the trajectory
"""
infos = super(PoseTrajectory3D, self).get_infos()
infos["duration (s)"] = self.timestamps[-1] - self.timestamps[0]
infos["t_start (s)"] = self.timestamps[0]
infos["t_end (s)"] = self.timestamps[-1]
return infos
|
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https://github.com/MichaelGrupp/evo/blob/c65af3b69188aaadbbd7b5f99ac7973d74343d65/evo/core/trajectory.py#L382-L390
|
|
redhat-performance/tuned
|
77f534993633e8e1c236ce9b05094aa3947a81ed
|
tuned-gui.py
|
python
|
Base.data_for_listbox_summary_of_active_profile
|
(self)
|
This add rows to object listbox_summary_of_active_profile.
Row consist of grid. Inside grid on first possition is label, second possition is vertical grid.
label = name of plugin
verical grid consist of labels where are stored values for plugin option and value.
This method is emited after change profile and on startup of app.
|
This add rows to object listbox_summary_of_active_profile.
Row consist of grid. Inside grid on first possition is label, second possition is vertical grid.
label = name of plugin
verical grid consist of labels where are stored values for plugin option and value.
|
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] |
def data_for_listbox_summary_of_active_profile(self):
"""
This add rows to object listbox_summary_of_active_profile.
Row consist of grid. Inside grid on first possition is label, second possition is vertical grid.
label = name of plugin
verical grid consist of labels where are stored values for plugin option and value.
This method is emited after change profile and on startup of app.
"""
for row in self._gobj('listboxSummaryOfActiveProfile'):
self._gobj('listboxSummaryOfActiveProfile').remove(row)
if self.is_tuned_connection_ok():
self.active_profile = \
self.manager.get_profile(self.controller.active_profile())
else:
self.active_profile = None
self._gobj('summaryProfileName').set_text(self.active_profile.name)
try:
self._gobj('summaryIncludedProfileName').set_text(self.active_profile.options['include'
])
except:
# keyerror probably
self._gobj('summaryIncludedProfileName').set_text('None')
row = Gtk.ListBoxRow()
box = Gtk.Box(orientation=Gtk.Orientation.HORIZONTAL, spacing=0)
plugin_name = Gtk.Label()
plugin_name.set_markup('<b>Plugin Name</b>')
plugin_option = Gtk.Label()
plugin_option.set_markup('<b>Plugin Options</b>')
box.pack_start(plugin_name, True, True, 0)
box.pack_start(plugin_option, True, True, 0)
row.add(box)
self._gobj('listboxSummaryOfActiveProfile').add(row)
sep = Gtk.Separator.new(Gtk.Orientation.HORIZONTAL)
self._gobj('listboxSummaryOfActiveProfile').add(sep)
sep.show()
for u in self.active_profile.units:
row = Gtk.ListBoxRow()
hbox = Gtk.Box(orientation=Gtk.Orientation.HORIZONTAL,
spacing=0)
hbox.set_homogeneous(True)
row.add(hbox)
label = Gtk.Label()
label.set_markup(u)
label.set_justify(Gtk.Justification.LEFT)
hbox.pack_start(label, False, True, 1)
grid = Gtk.Box(orientation=Gtk.Orientation.VERTICAL,
spacing=0)
grid.set_homogeneous(True)
for o in self.active_profile.units[u].options:
label_option = Gtk.Label()
label_option.set_markup(o + ' = ' + '<b>'
+ self.active_profile.units[u].options[o]
+ '</b>')
grid.pack_start(label_option, False, True, 0)
hbox.pack_start(grid, False, True, 0)
self._gobj('listboxSummaryOfActiveProfile').add(row)
separator = Gtk.Separator.new(Gtk.Orientation.HORIZONTAL)
self._gobj('listboxSummaryOfActiveProfile').add(separator)
separator.show()
self._gobj('listboxSummaryOfActiveProfile').show_all()
|
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] |
https://github.com/redhat-performance/tuned/blob/77f534993633e8e1c236ce9b05094aa3947a81ed/tuned-gui.py#L234-L305
|
||
castorini/castor
|
fa2f59535c71a0fb4586afbe543b81ba812c8630
|
datasets/trecqa.py
|
python
|
TRECQA.iters
|
(cls, path, vectors_name, vectors_dir, batch_size=64, shuffle=True, device=0, pt_file=False, vectors=None, unk_init=torch.Tensor.zero_)
|
return BucketIterator.splits((train, validation, test), batch_size=batch_size, repeat=False, shuffle=shuffle, sort_within_batch=True, device=device)
|
:param path: directory containing train, test, dev files
:param vectors_name: name of word vectors file
:param vectors_dir: directory containing word vectors file
:param batch_size: batch size
:param device: GPU device
:param vectors: custom vectors - either predefined torchtext vectors or your own custom Vector classes
:param unk_init: function used to generate vector for OOV words
:return:
|
:param path: directory containing train, test, dev files
:param vectors_name: name of word vectors file
:param vectors_dir: directory containing word vectors file
:param batch_size: batch size
:param device: GPU device
:param vectors: custom vectors - either predefined torchtext vectors or your own custom Vector classes
:param unk_init: function used to generate vector for OOV words
:return:
|
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":",
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] |
def iters(cls, path, vectors_name, vectors_dir, batch_size=64, shuffle=True, device=0, pt_file=False, vectors=None, unk_init=torch.Tensor.zero_):
"""
:param path: directory containing train, test, dev files
:param vectors_name: name of word vectors file
:param vectors_dir: directory containing word vectors file
:param batch_size: batch size
:param device: GPU device
:param vectors: custom vectors - either predefined torchtext vectors or your own custom Vector classes
:param unk_init: function used to generate vector for OOV words
:return:
"""
train, validation, test = cls.splits(path)
if not pt_file:
if vectors is None:
vectors = Vectors(name=vectors_name, cache=vectors_dir, unk_init=unk_init)
cls.TEXT_FIELD.build_vocab(train, validation, test, vectors=vectors)
else:
cls.TEXT_FIELD.build_vocab(train, validation, test)
cls.TEXT_FIELD = cls.set_vectors(cls.TEXT_FIELD, os.path.join(vectors_dir, vectors_name))
cls.LABEL_FIELD.build_vocab(train, validation, test)
cls.VOCAB_SIZE = len(cls.TEXT_FIELD.vocab)
return BucketIterator.splits((train, validation, test), batch_size=batch_size, repeat=False, shuffle=shuffle, sort_within_batch=True, device=device)
|
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"shuffle",
",",
"sort_within_batch",
"=",
"True",
",",
"device",
"=",
"device",
")"
] |
https://github.com/castorini/castor/blob/fa2f59535c71a0fb4586afbe543b81ba812c8630/datasets/trecqa.py#L37-L62
|
|
ctxis/CAPE
|
dae9fa6a254ecdbabeb7eb0d2389fa63722c1e82
|
modules/processing/parsers/mwcp/utils/pefileutils.py
|
python
|
obtain_physical_offset_x64
|
(rel_loc, inst_end_raw, pe=None, file_data=None)
|
For a 64-bit PE file, pointers to data elements are relative to the end of the assembly instruction. Therefore,
given a location (rel_loc) relative to the end of an instruction (inst_end_raw), convert the end instruction
address to a memory offset, add that value to the relative location of the data, and convert that to a raw
offset.
:param rel_loc: Location of data element relative to the end of the instruction address in inst_end_raw
:param inst_end_raw: End of an instruction address referencing the data for rel_loc
:param pe: pefile.PE object
:param file_data: Input file data
:return: Raw offset for the data, or None.
|
For a 64-bit PE file, pointers to data elements are relative to the end of the assembly instruction. Therefore,
given a location (rel_loc) relative to the end of an instruction (inst_end_raw), convert the end instruction
address to a memory offset, add that value to the relative location of the data, and convert that to a raw
offset.
|
[
"For",
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"64",
"-",
"bit",
"PE",
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"pointers",
"to",
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"elements",
"are",
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"the",
"data",
"and",
"convert",
"that",
"to",
"a",
"raw",
"offset",
"."
] |
def obtain_physical_offset_x64(rel_loc, inst_end_raw, pe=None, file_data=None):
"""
For a 64-bit PE file, pointers to data elements are relative to the end of the assembly instruction. Therefore,
given a location (rel_loc) relative to the end of an instruction (inst_end_raw), convert the end instruction
address to a memory offset, add that value to the relative location of the data, and convert that to a raw
offset.
:param rel_loc: Location of data element relative to the end of the instruction address in inst_end_raw
:param inst_end_raw: End of an instruction address referencing the data for rel_loc
:param pe: pefile.PE object
:param file_data: Input file data
:return: Raw offset for the data, or None.
"""
if file_data:
pe = obtain_pe(file_data)
if pe:
inst_end_mem = obtain_memory_offset(inst_end_raw, pe=pe)
# Obtain the memory location of the data and convert it to a physical offset
mem_loc = rel_loc + inst_end_mem
return obtain_physical_offset(mem_loc, pe=pe)
else:
return None
|
[
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"pe",
")",
"else",
":",
"return",
"None"
] |
https://github.com/ctxis/CAPE/blob/dae9fa6a254ecdbabeb7eb0d2389fa63722c1e82/modules/processing/parsers/mwcp/utils/pefileutils.py#L134-L156
|
||
theotherp/nzbhydra
|
4b03d7f769384b97dfc60dade4806c0fc987514e
|
libs/bs4/dammit.py
|
python
|
EntitySubstitution.substitute_xml_containing_entities
|
(
cls, value, make_quoted_attribute=False)
|
return value
|
Substitute XML entities for special XML characters.
:param value: A string to be substituted. The less-than sign will
become <, the greater-than sign will become >, and any
ampersands that are not part of an entity defition will
become &.
:param make_quoted_attribute: If True, then the string will be
quoted, as befits an attribute value.
|
Substitute XML entities for special XML characters.
|
[
"Substitute",
"XML",
"entities",
"for",
"special",
"XML",
"characters",
"."
] |
def substitute_xml_containing_entities(
cls, value, make_quoted_attribute=False):
"""Substitute XML entities for special XML characters.
:param value: A string to be substituted. The less-than sign will
become <, the greater-than sign will become >, and any
ampersands that are not part of an entity defition will
become &.
:param make_quoted_attribute: If True, then the string will be
quoted, as befits an attribute value.
"""
# Escape angle brackets, and ampersands that aren't part of
# entities.
value = cls.BARE_AMPERSAND_OR_BRACKET.sub(
cls._substitute_xml_entity, value)
if make_quoted_attribute:
value = cls.quoted_attribute_value(value)
return value
|
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"def",
"substitute_xml_containing_entities",
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"cls",
",",
"value",
",",
"make_quoted_attribute",
"=",
"False",
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"# Escape angle brackets, and ampersands that aren't part of",
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"value",
"=",
"cls",
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"quoted_attribute_value",
"(",
"value",
")",
"return",
"value"
] |
https://github.com/theotherp/nzbhydra/blob/4b03d7f769384b97dfc60dade4806c0fc987514e/libs/bs4/dammit.py#L161-L180
|
|
IronLanguages/ironpython3
|
7a7bb2a872eeab0d1009fc8a6e24dca43f65b693
|
Src/StdLib/Lib/lib2to3/pytree.py
|
python
|
BasePattern.match
|
(self, node, results=None)
|
return True
|
Does this pattern exactly match a node?
Returns True if it matches, False if not.
If results is not None, it must be a dict which will be
updated with the nodes matching named subpatterns.
Default implementation for non-wildcard patterns.
|
Does this pattern exactly match a node?
|
[
"Does",
"this",
"pattern",
"exactly",
"match",
"a",
"node?"
] |
def match(self, node, results=None):
"""
Does this pattern exactly match a node?
Returns True if it matches, False if not.
If results is not None, it must be a dict which will be
updated with the nodes matching named subpatterns.
Default implementation for non-wildcard patterns.
"""
if self.type is not None and node.type != self.type:
return False
if self.content is not None:
r = None
if results is not None:
r = {}
if not self._submatch(node, r):
return False
if r:
results.update(r)
if results is not None and self.name:
results[self.name] = node
return True
|
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"def",
"match",
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"=",
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".",
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":",
"results",
"[",
"self",
".",
"name",
"]",
"=",
"node",
"return",
"True"
] |
https://github.com/IronLanguages/ironpython3/blob/7a7bb2a872eeab0d1009fc8a6e24dca43f65b693/Src/StdLib/Lib/lib2to3/pytree.py#L455-L478
|
|
conansherry/detectron2
|
72c935d9aad8935406b1038af408aa06077d950a
|
detectron2/modeling/backbone/build.py
|
python
|
build_backbone
|
(cfg, input_shape=None)
|
return backbone
|
Build a backbone from `cfg.MODEL.BACKBONE.NAME`.
Returns:
an instance of :class:`Backbone`
|
Build a backbone from `cfg.MODEL.BACKBONE.NAME`.
|
[
"Build",
"a",
"backbone",
"from",
"cfg",
".",
"MODEL",
".",
"BACKBONE",
".",
"NAME",
"."
] |
def build_backbone(cfg, input_shape=None):
"""
Build a backbone from `cfg.MODEL.BACKBONE.NAME`.
Returns:
an instance of :class:`Backbone`
"""
if input_shape is None:
input_shape = ShapeSpec(channels=len(cfg.MODEL.PIXEL_MEAN))
backbone_name = cfg.MODEL.BACKBONE.NAME
backbone = BACKBONE_REGISTRY.get(backbone_name)(cfg, input_shape)
assert isinstance(backbone, Backbone)
return backbone
|
[
"def",
"build_backbone",
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"cfg",
",",
"input_shape",
"=",
"None",
")",
":",
"if",
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",",
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https://github.com/conansherry/detectron2/blob/72c935d9aad8935406b1038af408aa06077d950a/detectron2/modeling/backbone/build.py#L20-L33
|
|
zhl2008/awd-platform
|
0416b31abea29743387b10b3914581fbe8e7da5e
|
web_flaskbb/lib/python2.7/site-packages/whoosh/searching.py
|
python
|
Hit.itervalues
|
(self)
|
return itervalues(self.fields())
|
[] |
def itervalues(self):
return itervalues(self.fields())
|
[
"def",
"itervalues",
"(",
"self",
")",
":",
"return",
"itervalues",
"(",
"self",
".",
"fields",
"(",
")",
")"
] |
https://github.com/zhl2008/awd-platform/blob/0416b31abea29743387b10b3914581fbe8e7da5e/web_flaskbb/lib/python2.7/site-packages/whoosh/searching.py#L1534-L1535
|
|||
aws/aws-sam-cli
|
2aa7bf01b2e0b0864ef63b1898a8b30577443acc
|
samcli/lib/sync/sync_flow.py
|
python
|
SyncFlow.__init__
|
(
self,
build_context: "BuildContext",
deploy_context: "DeployContext",
physical_id_mapping: Dict[str, str],
log_name: str,
stacks: Optional[List[Stack]] = None,
)
|
Parameters
----------
build_context : BuildContext
BuildContext used for build related parameters
deploy_context : BuildContext
DeployContext used for this deploy related parameters
physical_id_mapping : Dict[str, str]
Mapping between resource logical identifier and physical identifier
log_name : str
Name to be used for logging purposes
stacks : List[Stack], optional
List of stacks containing a root stack and optional nested stacks
|
Parameters
----------
build_context : BuildContext
BuildContext used for build related parameters
deploy_context : BuildContext
DeployContext used for this deploy related parameters
physical_id_mapping : Dict[str, str]
Mapping between resource logical identifier and physical identifier
log_name : str
Name to be used for logging purposes
stacks : List[Stack], optional
List of stacks containing a root stack and optional nested stacks
|
[
"Parameters",
"----------",
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":",
"BuildContext",
"BuildContext",
"used",
"for",
"build",
"related",
"parameters",
"deploy_context",
":",
"BuildContext",
"DeployContext",
"used",
"for",
"this",
"deploy",
"related",
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"physical_id_mapping",
":",
"Dict",
"[",
"str",
"str",
"]",
"Mapping",
"between",
"resource",
"logical",
"identifier",
"and",
"physical",
"identifier",
"log_name",
":",
"str",
"Name",
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"be",
"used",
"for",
"logging",
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"stacks",
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"[",
"Stack",
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"optional",
"List",
"of",
"stacks",
"containing",
"a",
"root",
"stack",
"and",
"optional",
"nested",
"stacks"
] |
def __init__(
self,
build_context: "BuildContext",
deploy_context: "DeployContext",
physical_id_mapping: Dict[str, str],
log_name: str,
stacks: Optional[List[Stack]] = None,
):
"""
Parameters
----------
build_context : BuildContext
BuildContext used for build related parameters
deploy_context : BuildContext
DeployContext used for this deploy related parameters
physical_id_mapping : Dict[str, str]
Mapping between resource logical identifier and physical identifier
log_name : str
Name to be used for logging purposes
stacks : List[Stack], optional
List of stacks containing a root stack and optional nested stacks
"""
self._build_context = build_context
self._deploy_context = deploy_context
self._log_name = log_name
self._stacks = stacks
self._session = None
self._physical_id_mapping = physical_id_mapping
self._locks = None
|
[
"def",
"__init__",
"(",
"self",
",",
"build_context",
":",
"\"BuildContext\"",
",",
"deploy_context",
":",
"\"DeployContext\"",
",",
"physical_id_mapping",
":",
"Dict",
"[",
"str",
",",
"str",
"]",
",",
"log_name",
":",
"str",
",",
"stacks",
":",
"Optional",
"[",
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"[",
"Stack",
"]",
"]",
"=",
"None",
",",
")",
":",
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"_build_context",
"=",
"build_context",
"self",
".",
"_deploy_context",
"=",
"deploy_context",
"self",
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"log_name",
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"_stacks",
"=",
"stacks",
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"None",
"self",
".",
"_physical_id_mapping",
"=",
"physical_id_mapping",
"self",
".",
"_locks",
"=",
"None"
] |
https://github.com/aws/aws-sam-cli/blob/2aa7bf01b2e0b0864ef63b1898a8b30577443acc/samcli/lib/sync/sync_flow.py#L43-L71
|
||
glitchdotcom/WebPutty
|
4f5da5eb2b4668cbf3c15cf002feacd1d95d2ef7
|
ziplibs/BeautifulSoup.py
|
python
|
Tag.__nonzero__
|
(self)
|
return True
|
A tag is non-None even if it has no contents.
|
A tag is non-None even if it has no contents.
|
[
"A",
"tag",
"is",
"non",
"-",
"None",
"even",
"if",
"it",
"has",
"no",
"contents",
"."
] |
def __nonzero__(self):
"A tag is non-None even if it has no contents."
return True
|
[
"def",
"__nonzero__",
"(",
"self",
")",
":",
"return",
"True"
] |
https://github.com/glitchdotcom/WebPutty/blob/4f5da5eb2b4668cbf3c15cf002feacd1d95d2ef7/ziplibs/BeautifulSoup.py#L614-L616
|
|
HumanDynamics/openPDS
|
20d9e0669b0f120399055765b61f0f1fa298a1ff
|
openpds/connectors/funf/views.py
|
python
|
clean_keys
|
(d)
|
return new
|
replace all "." with "-" and force keys to lowercase
|
replace all "." with "-" and force keys to lowercase
|
[
"replace",
"all",
".",
"with",
"-",
"and",
"force",
"keys",
"to",
"lowercase"
] |
def clean_keys(d):
'''replace all "." with "-" and force keys to lowercase'''
new = {}
for k, v in d.iteritems():
if isinstance(v, dict):
v = clean_keys(v)
if isinstance(v, list):
for idx,i in enumerate(v):
if isinstance(i, dict):
v[idx] = clean_keys(i)
new[k.replace('.', '-').lower()] = v
return new
|
[
"def",
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"(",
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")",
":",
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"=",
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"}",
"for",
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",",
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".",
"iteritems",
"(",
")",
":",
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",",
"'-'",
")",
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"lower",
"(",
")",
"]",
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"v",
"return",
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] |
https://github.com/HumanDynamics/openPDS/blob/20d9e0669b0f120399055765b61f0f1fa298a1ff/openpds/connectors/funf/views.py#L146-L157
|
|
chrysn/aiocoap
|
1f03d4ceb969b2b443c288c312d44c3b7c3e2031
|
aiocoap/pipe.py
|
python
|
Pipe.poke
|
(self)
|
Ask the responder for a life sign. It is up to the responder to
ignore this (eg. because the responder is the library/application and
can't be just gone), to issue a generic transport-dependent 'ping' to
see whether the connection is still alive, or to retransmit the request
if it is an observation over an unreliable channel.
In any case, no status is reported directly to the poke, but if
whatever the responder does fails, it will send an appropriate error
message as a response.
|
Ask the responder for a life sign. It is up to the responder to
ignore this (eg. because the responder is the library/application and
can't be just gone), to issue a generic transport-dependent 'ping' to
see whether the connection is still alive, or to retransmit the request
if it is an observation over an unreliable channel.
|
[
"Ask",
"the",
"responder",
"for",
"a",
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"request",
"if",
"it",
"is",
"an",
"observation",
"over",
"an",
"unreliable",
"channel",
"."
] |
def poke(self):
"""Ask the responder for a life sign. It is up to the responder to
ignore this (eg. because the responder is the library/application and
can't be just gone), to issue a generic transport-dependent 'ping' to
see whether the connection is still alive, or to retransmit the request
if it is an observation over an unreliable channel.
In any case, no status is reported directly to the poke, but if
whatever the responder does fails, it will send an appropriate error
message as a response."""
raise NotImplementedError()
|
[
"def",
"poke",
"(",
"self",
")",
":",
"raise",
"NotImplementedError",
"(",
")"
] |
https://github.com/chrysn/aiocoap/blob/1f03d4ceb969b2b443c288c312d44c3b7c3e2031/aiocoap/pipe.py#L90-L100
|
||
vertical-knowledge/ripozo
|
e648db2967c4fbf4315860c21a8418f384db4454
|
ripozo/adapters/jsonapi.py
|
python
|
JSONAPIAdapter._construct_links
|
(self, resource)
|
return links
|
Constructs the links object according
to `this section <http://jsonapi.org/format/#document-links>`_
:param ResourceBase resource: The links from this resource
instance will be used to construct the links object.
:return: A dictionary representing the links object
:rtype: dict
|
Constructs the links object according
to `this section <http://jsonapi.org/format/#document-links>`_
|
[
"Constructs",
"the",
"links",
"object",
"according",
"to",
"this",
"section",
"<http",
":",
"//",
"jsonapi",
".",
"org",
"/",
"format",
"/",
"#document",
"-",
"links",
">",
"_"
] |
def _construct_links(self, resource):
"""
Constructs the links object according
to `this section <http://jsonapi.org/format/#document-links>`_
:param ResourceBase resource: The links from this resource
instance will be used to construct the links object.
:return: A dictionary representing the links object
:rtype: dict
"""
self_url = self.combine_base_url_with_resource_url(resource.url)
links = {'self': self_url}
for link, name, embedded in resource.linked_resources:
links[name] = self.combine_base_url_with_resource_url(link.url)
return links
|
[
"def",
"_construct_links",
"(",
"self",
",",
"resource",
")",
":",
"self_url",
"=",
"self",
".",
"combine_base_url_with_resource_url",
"(",
"resource",
".",
"url",
")",
"links",
"=",
"{",
"'self'",
":",
"self_url",
"}",
"for",
"link",
",",
"name",
",",
"embedded",
"in",
"resource",
".",
"linked_resources",
":",
"links",
"[",
"name",
"]",
"=",
"self",
".",
"combine_base_url_with_resource_url",
"(",
"link",
".",
"url",
")",
"return",
"links"
] |
https://github.com/vertical-knowledge/ripozo/blob/e648db2967c4fbf4315860c21a8418f384db4454/ripozo/adapters/jsonapi.py#L67-L81
|
|
MartinThoma/algorithms
|
6199cfa3446e1056c7b4d75ca6e306e9e56fd95b
|
bib/scrape.py
|
python
|
add_data
|
(path_to_db, data, table)
|
Add the data to the database.
|
Add the data to the database.
|
[
"Add",
"the",
"data",
"to",
"the",
"database",
"."
] |
def add_data(path_to_db, data, table):
"""Add the data to the database."""
con = sqlite3.connect(path_to_db)
cur = con.cursor()
for el in data:
if table in ['seatestimate', 'manualcount']:
sql = ("INSERT INTO `{table}` "
"(`date_str`, `timezone_type`, `timezone`, "
"`location_name`, "
"`free_seats`, `occupied_seats`) "
"VALUES ('{date}', '{timezone_type}', "
"'{timezone}', '{location_name}',"
"'{free_seats}', '{occupied_seats}');"
"").format(table=table,
date=el['timestamp']['date'],
timezone_type=el['timestamp']['timezone_type'],
timezone=el['timestamp']['timezone'],
location_name=el['location_name'],
occupied_seats=el['occupied_seats'],
free_seats=el['free_seats'])
else:
row_counter = 'number_of_ports'
if table == 'wlanclients':
row_counter = 'number_of_clients'
sql = ("INSERT INTO `{table}` "
"(`date_str`, `timezone_type`, `timezone`, "
"`location_name`, `{row_counter}`) "
"VALUES ('{date}', '{timezone_type}', "
"'{timezone}', '{location_name}',"
"'{counter}');"
"").format(table=table,
row_counter=row_counter,
date=el['timestamp']['date'],
timezone_type=el['timestamp']['timezone_type'],
timezone=el['timestamp']['timezone'],
location_name=el['location_name'],
counter=el[row_counter])
try:
cur.execute(sql)
except sqlite3.IntegrityError:
pass # This data is already in the DB. Just ignore it.
con.commit()
con.close()
|
[
"def",
"add_data",
"(",
"path_to_db",
",",
"data",
",",
"table",
")",
":",
"con",
"=",
"sqlite3",
".",
"connect",
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"path_to_db",
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"'seatestimate'",
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"\"INSERT INTO `{table}` \"",
"\"(`date_str`, `timezone_type`, `timezone`, \"",
"\"`location_name`, \"",
"\"`free_seats`, `occupied_seats`) \"",
"\"VALUES ('{date}', '{timezone_type}', \"",
"\"'{timezone}', '{location_name}',\"",
"\"'{free_seats}', '{occupied_seats}');\"",
"\"\"",
")",
".",
"format",
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"table",
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"'timestamp'",
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"free_seats",
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"(",
"\"INSERT INTO `{table}` \"",
"\"(`date_str`, `timezone_type`, `timezone`, \"",
"\"`location_name`, `{row_counter}`) \"",
"\"VALUES ('{date}', '{timezone_type}', \"",
"\"'{timezone}', '{location_name}',\"",
"\"'{counter}');\"",
"\"\"",
")",
".",
"format",
"(",
"table",
"=",
"table",
",",
"row_counter",
"=",
"row_counter",
",",
"date",
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"el",
"[",
"'timestamp'",
"]",
"[",
"'date'",
"]",
",",
"timezone_type",
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"el",
"[",
"'timestamp'",
"]",
"[",
"'timezone_type'",
"]",
",",
"timezone",
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"el",
"[",
"'timestamp'",
"]",
"[",
"'timezone'",
"]",
",",
"location_name",
"=",
"el",
"[",
"'location_name'",
"]",
",",
"counter",
"=",
"el",
"[",
"row_counter",
"]",
")",
"try",
":",
"cur",
".",
"execute",
"(",
"sql",
")",
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"sqlite3",
".",
"IntegrityError",
":",
"pass",
"# This data is already in the DB. Just ignore it.",
"con",
".",
"commit",
"(",
")",
"con",
".",
"close",
"(",
")"
] |
https://github.com/MartinThoma/algorithms/blob/6199cfa3446e1056c7b4d75ca6e306e9e56fd95b/bib/scrape.py#L111-L154
|
||
chrisconlan/algorithmic-trading-with-python
|
ebe01087c7d9172db72bc3c9adc1eee5e882ac49
|
src/pypm/portfolio.py
|
python
|
Position.__init__
|
(self, symbol: Symbol, entry_date: pd.Timestamp,
entry_price: Dollars, shares: int)
|
Equivalent to buying a certain number of shares of the asset
|
Equivalent to buying a certain number of shares of the asset
|
[
"Equivalent",
"to",
"buying",
"a",
"certain",
"number",
"of",
"shares",
"of",
"the",
"asset"
] |
def __init__(self, symbol: Symbol, entry_date: pd.Timestamp,
entry_price: Dollars, shares: int):
"""
Equivalent to buying a certain number of shares of the asset
"""
# Recorded on initialization
self.entry_date = entry_date
assert entry_price > 0, 'Cannot buy asset with zero or negative price.'
self.entry_price = entry_price
assert shares > 0, 'Cannot buy zero or negative shares.'
self.shares = shares
self.symbol = symbol
# Recorded on position exit
self.exit_date: pd.Timestamp = None
self.exit_price: Dollars = None
# For easily getting current portfolio value
self.last_date: pd.Timestamp = None
self.last_price: Dollars = None
# Updated intermediately
self._dict_series: Dict[pd.Timestamp, Dollars] = OrderedDict()
self.record_price_update(entry_date, entry_price)
# Cache control for pd.Series representation
self._price_series: pd.Series = None
self._needs_update_pd_series: bool = True
|
[
"def",
"__init__",
"(",
"self",
",",
"symbol",
":",
"Symbol",
",",
"entry_date",
":",
"pd",
".",
"Timestamp",
",",
"entry_price",
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"Dollars",
",",
"shares",
":",
"int",
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":",
"# Recorded on initialization",
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"entry_date",
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",",
"'Cannot buy asset with zero or negative price.'",
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"'Cannot buy zero or negative shares.'",
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".",
"exit_price",
":",
"Dollars",
"=",
"None",
"# For easily getting current portfolio value",
"self",
".",
"last_date",
":",
"pd",
".",
"Timestamp",
"=",
"None",
"self",
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"last_price",
":",
"Dollars",
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"# Updated intermediately",
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":",
"Dict",
"[",
"pd",
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"Timestamp",
",",
"Dollars",
"]",
"=",
"OrderedDict",
"(",
")",
"self",
".",
"record_price_update",
"(",
"entry_date",
",",
"entry_price",
")",
"# Cache control for pd.Series representation",
"self",
".",
"_price_series",
":",
"pd",
".",
"Series",
"=",
"None",
"self",
".",
"_needs_update_pd_series",
":",
"bool",
"=",
"True"
] |
https://github.com/chrisconlan/algorithmic-trading-with-python/blob/ebe01087c7d9172db72bc3c9adc1eee5e882ac49/src/pypm/portfolio.py#L29-L60
|
||
Coalfire-Research/Slackor
|
aa32a7f9250bd8b107d48fd573f26176b527b2a5
|
impacket/impacket/dcerpc/v5/enum.py
|
python
|
_is_sunder
|
(name)
|
return (name[0] == name[-1] == '_' and
name[1:2] != '_' and
name[-2:-1] != '_' and
len(name) > 2)
|
Returns True if a _sunder_ name, False otherwise.
|
Returns True if a _sunder_ name, False otherwise.
|
[
"Returns",
"True",
"if",
"a",
"_sunder_",
"name",
"False",
"otherwise",
"."
] |
def _is_sunder(name):
"""Returns True if a _sunder_ name, False otherwise."""
return (name[0] == name[-1] == '_' and
name[1:2] != '_' and
name[-2:-1] != '_' and
len(name) > 2)
|
[
"def",
"_is_sunder",
"(",
"name",
")",
":",
"return",
"(",
"name",
"[",
"0",
"]",
"==",
"name",
"[",
"-",
"1",
"]",
"==",
"'_'",
"and",
"name",
"[",
"1",
":",
"2",
"]",
"!=",
"'_'",
"and",
"name",
"[",
"-",
"2",
":",
"-",
"1",
"]",
"!=",
"'_'",
"and",
"len",
"(",
"name",
")",
">",
"2",
")"
] |
https://github.com/Coalfire-Research/Slackor/blob/aa32a7f9250bd8b107d48fd573f26176b527b2a5/impacket/impacket/dcerpc/v5/enum.py#L59-L64
|
|
cheshirekow/cmake_format
|
eff5df1f41c665ea7cac799396042e4f406ef09a
|
cmakelang/format/formatter.py
|
python
|
StackContext.push_node
|
(self, node)
|
Push `node` onto the `node_path` and yield a context manager. Pop `node`
off of `node_path` when the context manager `__exit__()s`
|
Push `node` onto the `node_path` and yield a context manager. Pop `node`
off of `node_path` when the context manager `__exit__()s`
|
[
"Push",
"node",
"onto",
"the",
"node_path",
"and",
"yield",
"a",
"context",
"manager",
".",
"Pop",
"node",
"off",
"of",
"node_path",
"when",
"the",
"context",
"manager",
"__exit__",
"()",
"s"
] |
def push_node(self, node):
"""
Push `node` onto the `node_path` and yield a context manager. Pop `node`
off of `node_path` when the context manager `__exit__()s`
"""
self.node_path.append(node)
yield None
self.node_path.pop(-1)
|
[
"def",
"push_node",
"(",
"self",
",",
"node",
")",
":",
"self",
".",
"node_path",
".",
"append",
"(",
"node",
")",
"yield",
"None",
"self",
".",
"node_path",
".",
"pop",
"(",
"-",
"1",
")"
] |
https://github.com/cheshirekow/cmake_format/blob/eff5df1f41c665ea7cac799396042e4f406ef09a/cmakelang/format/formatter.py#L288-L295
|
||
frePPLe/frepple
|
57aa612030b4fcd03cb9c613f83a7dac4f0e8d6d
|
freppledb/common/report.py
|
python
|
getCurrency
|
()
|
[] |
def getCurrency():
try:
cur = Parameter.getValue("currency").split(",")
if len(cur) < 2:
return ("", " %s" % escape(cur[0]))
else:
return ("%s " % escape(cur[0]), " %s" % escape(cur[1]))
except Exception:
return ("", " $")
|
[
"def",
"getCurrency",
"(",
")",
":",
"try",
":",
"cur",
"=",
"Parameter",
".",
"getValue",
"(",
"\"currency\"",
")",
".",
"split",
"(",
"\",\"",
")",
"if",
"len",
"(",
"cur",
")",
"<",
"2",
":",
"return",
"(",
"\"\"",
",",
"\" %s\"",
"%",
"escape",
"(",
"cur",
"[",
"0",
"]",
")",
")",
"else",
":",
"return",
"(",
"\"%s \"",
"%",
"escape",
"(",
"cur",
"[",
"0",
"]",
")",
",",
"\" %s\"",
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"escape",
"(",
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"[",
"1",
"]",
")",
")",
"except",
"Exception",
":",
"return",
"(",
"\"\"",
",",
"\" $\"",
")"
] |
https://github.com/frePPLe/frepple/blob/57aa612030b4fcd03cb9c613f83a7dac4f0e8d6d/freppledb/common/report.py#L455-L463
|
||||
jupyter-widgets/ipyleaflet
|
3970dc74861d17eca56824eb5bf93bafe156319e
|
ipyleaflet/leaflet.py
|
python
|
Marker.on_move
|
(self, callback, remove=False)
|
Add a move event listener.
Parameters
----------
callback : callable
Callback function that will be called on move event.
remove: boolean
Whether to remove this callback or not. Defaults to False.
|
Add a move event listener.
|
[
"Add",
"a",
"move",
"event",
"listener",
"."
] |
def on_move(self, callback, remove=False):
"""Add a move event listener.
Parameters
----------
callback : callable
Callback function that will be called on move event.
remove: boolean
Whether to remove this callback or not. Defaults to False.
"""
self._move_callbacks.register_callback(callback, remove=remove)
|
[
"def",
"on_move",
"(",
"self",
",",
"callback",
",",
"remove",
"=",
"False",
")",
":",
"self",
".",
"_move_callbacks",
".",
"register_callback",
"(",
"callback",
",",
"remove",
"=",
"remove",
")"
] |
https://github.com/jupyter-widgets/ipyleaflet/blob/3970dc74861d17eca56824eb5bf93bafe156319e/ipyleaflet/leaflet.py#L434-L444
|
||
home-assistant/core
|
265ebd17a3f17ed8dc1e9bdede03ac8e323f1ab1
|
homeassistant/components/elkm1/alarm_control_panel.py
|
python
|
ElkArea.changed_by
|
(self)
|
return self._changed_by
|
Last change triggered by.
|
Last change triggered by.
|
[
"Last",
"change",
"triggered",
"by",
"."
] |
def changed_by(self):
"""Last change triggered by."""
return self._changed_by
|
[
"def",
"changed_by",
"(",
"self",
")",
":",
"return",
"self",
".",
"_changed_by"
] |
https://github.com/home-assistant/core/blob/265ebd17a3f17ed8dc1e9bdede03ac8e323f1ab1/homeassistant/components/elkm1/alarm_control_panel.py#L198-L200
|
|
naszilla/bananas
|
e2c12ade9e290e309e206fc3c8f97a373a136a81
|
bo/pp/pp_gp_my_distmat.py
|
python
|
MyGpDistmatPP.set_data
|
(self, data)
|
Set self.data
|
Set self.data
|
[
"Set",
"self",
".",
"data"
] |
def set_data(self, data):
""" Set self.data """
if data is None:
pass #TODO
self.data_init = copy.deepcopy(data)
self.data = copy.deepcopy(self.data_init)
|
[
"def",
"set_data",
"(",
"self",
",",
"data",
")",
":",
"if",
"data",
"is",
"None",
":",
"pass",
"#TODO",
"self",
".",
"data_init",
"=",
"copy",
".",
"deepcopy",
"(",
"data",
")",
"self",
".",
"data",
"=",
"copy",
".",
"deepcopy",
"(",
"self",
".",
"data_init",
")"
] |
https://github.com/naszilla/bananas/blob/e2c12ade9e290e309e206fc3c8f97a373a136a81/bo/pp/pp_gp_my_distmat.py#L36-L41
|
||
Chaffelson/nipyapi
|
d3b186fd701ce308c2812746d98af9120955e810
|
nipyapi/nifi/models/drop_request_dto.py
|
python
|
DropRequestDTO.submission_time
|
(self, submission_time)
|
Sets the submission_time of this DropRequestDTO.
The timestamp when the query was submitted.
:param submission_time: The submission_time of this DropRequestDTO.
:type: str
|
Sets the submission_time of this DropRequestDTO.
The timestamp when the query was submitted.
|
[
"Sets",
"the",
"submission_time",
"of",
"this",
"DropRequestDTO",
".",
"The",
"timestamp",
"when",
"the",
"query",
"was",
"submitted",
"."
] |
def submission_time(self, submission_time):
"""
Sets the submission_time of this DropRequestDTO.
The timestamp when the query was submitted.
:param submission_time: The submission_time of this DropRequestDTO.
:type: str
"""
self._submission_time = submission_time
|
[
"def",
"submission_time",
"(",
"self",
",",
"submission_time",
")",
":",
"self",
".",
"_submission_time",
"=",
"submission_time"
] |
https://github.com/Chaffelson/nipyapi/blob/d3b186fd701ce308c2812746d98af9120955e810/nipyapi/nifi/models/drop_request_dto.py#L189-L198
|
||
meduza-corp/interstellar
|
40a801ccd7856491726f5a126621d9318cabe2e1
|
gsutil/gslib/copy_helper.py
|
python
|
_AppendComponentTrackerToParallelUploadTrackerFile
|
(tracker_file, component,
tracker_file_lock)
|
Appends info about the uploaded component to an existing tracker file.
Follows the format described in _CreateParallelUploadTrackerFile.
Args:
tracker_file: Tracker file to append to.
component: Component that was uploaded.
tracker_file_lock: Thread and process-safe Lock for the tracker file.
|
Appends info about the uploaded component to an existing tracker file.
|
[
"Appends",
"info",
"about",
"the",
"uploaded",
"component",
"to",
"an",
"existing",
"tracker",
"file",
"."
] |
def _AppendComponentTrackerToParallelUploadTrackerFile(tracker_file, component,
tracker_file_lock):
"""Appends info about the uploaded component to an existing tracker file.
Follows the format described in _CreateParallelUploadTrackerFile.
Args:
tracker_file: Tracker file to append to.
component: Component that was uploaded.
tracker_file_lock: Thread and process-safe Lock for the tracker file.
"""
lines = _GetParallelUploadTrackerFileLinesForComponents([component])
lines = [line + '\n' for line in lines]
with tracker_file_lock:
with open(tracker_file, 'a') as f:
f.writelines(lines)
|
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https://github.com/meduza-corp/interstellar/blob/40a801ccd7856491726f5a126621d9318cabe2e1/gsutil/gslib/copy_helper.py#L2630-L2645
|
||
uber-research/PPLM
|
e236b8989322128360182d29a79944627957ad47
|
paper_code/pytorch_pretrained_bert/optimization_openai.py
|
python
|
warmup_constant
|
(x, warmup=0.002)
|
return 1.0
|
Linearly increases learning rate over `warmup`*`t_total` (as provided to OpenAIAdam) training steps.
Learning rate is 1. afterwards.
|
Linearly increases learning rate over `warmup`*`t_total` (as provided to OpenAIAdam) training steps.
Learning rate is 1. afterwards.
|
[
"Linearly",
"increases",
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"rate",
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"OpenAIAdam",
")",
"training",
"steps",
".",
"Learning",
"rate",
"is",
"1",
".",
"afterwards",
"."
] |
def warmup_constant(x, warmup=0.002):
""" Linearly increases learning rate over `warmup`*`t_total` (as provided to OpenAIAdam) training steps.
Learning rate is 1. afterwards. """
if x < warmup:
return x/warmup
return 1.0
|
[
"def",
"warmup_constant",
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",",
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":",
"if",
"x",
"<",
"warmup",
":",
"return",
"x",
"/",
"warmup",
"return",
"1.0"
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https://github.com/uber-research/PPLM/blob/e236b8989322128360182d29a79944627957ad47/paper_code/pytorch_pretrained_bert/optimization_openai.py#L32-L37
|
|
algorhythms/LeetCode
|
3fb14aeea62a960442e47dfde9f964c7ffce32be
|
394 Decode String.py
|
python
|
SolutionError.decodeString
|
(self, s)
|
return ''.join(ret)
|
:type s: str
:rtype: str
|
:type s: str
:rtype: str
|
[
":",
"type",
"s",
":",
"str",
":",
"rtype",
":",
"str"
] |
def decodeString(self, s):
"""
:type s: str
:rtype: str
"""
stk = []
i = 0
ret = []
while i < len(s):
if s[i].isdigit():
j = i + 1
while s[j] != '[': j += 1
prev = stk[-1] if stk else 1
stk.append(prev * int(s[i:j]))
i = j + 1
elif s[i].islower():
repeat = stk[-1] if stk else 1
for _ in xrange(repeat): ret.append(s[i])
i += 1
elif s[i] == ']':
stk.pop()
i += 1
return ''.join(ret)
|
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https://github.com/algorhythms/LeetCode/blob/3fb14aeea62a960442e47dfde9f964c7ffce32be/394 Decode String.py#L88-L111
|
|
giantbranch/python-hacker-code
|
addbc8c73e7e6fb9e4fcadcec022fa1d3da4b96d
|
我手敲的代码(中文注释)/chapter11/volatility-2.3/volatility/commands.py
|
python
|
Command.table_header
|
(self, outfd, title_format_list = None)
|
Table header renders the title row of a table
This also stores the header types to ensure
everything is formatted appropriately.
It must be a list of tuples rather than a dict for ordering purposes.
|
Table header renders the title row of a table
|
[
"Table",
"header",
"renders",
"the",
"title",
"row",
"of",
"a",
"table"
] |
def table_header(self, outfd, title_format_list = None):
"""Table header renders the title row of a table
This also stores the header types to ensure
everything is formatted appropriately.
It must be a list of tuples rather than a dict for ordering purposes.
"""
titles = []
rules = []
self._formatlist = []
profile = addrspace.BufferAddressSpace(self._config).profile
for (k, v) in title_format_list:
spec = fmtspec.FormatSpec(self._formatlookup(profile, v))
# If spec.minwidth = -1, this field is unbounded length
if spec.minwidth != -1:
spec.minwidth = max(spec.minwidth, len(k))
# Get the title specification to follow the alignment of the field
titlespec = fmtspec.FormatSpec(formtype = 's', minwidth = max(spec.minwidth, len(k)))
titlespec.align = spec.align if spec.align in "<>^" else "<"
# Add this to the titles, rules, and formatspecs lists
titles.append(("{0:" + titlespec.to_string() + "}").format(k))
rules.append("-" * titlespec.minwidth)
self._formatlist.append(spec)
# Write out the titles and line rules
if outfd:
outfd.write(self.tablesep.join(titles) + "\n")
outfd.write(self.tablesep.join(rules) + "\n")
|
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https://github.com/giantbranch/python-hacker-code/blob/addbc8c73e7e6fb9e4fcadcec022fa1d3da4b96d/我手敲的代码(中文注释)/chapter11/volatility-2.3/volatility/commands.py#L164-L194
|
||
peter-u-diehl/stdp-mnist
|
d527ca3ee579d4f156d25ff160c0551a5ab82cf1
|
Diehl&Cook_MNIST_random_conn_generator.py
|
python
|
create_weights
|
()
|
[] |
def create_weights():
nInput = 784
nE = 400
nI = nE
dataPath = './random/'
weight = {}
weight['ee_input'] = 0.3
weight['ei_input'] = 0.2
weight['ee'] = 0.1
weight['ei'] = 10.4
weight['ie'] = 17.0
weight['ii'] = 0.4
pConn = {}
pConn['ee_input'] = 1.0
pConn['ei_input'] = 0.1
pConn['ee'] = 1.0
pConn['ei'] = 0.0025
pConn['ie'] = 0.9
pConn['ii'] = 0.1
print 'create random connection matrices'
connNameList = ['XeAe']
for name in connNameList:
weightMatrix = np.random.random((nInput, nE)) + 0.01
weightMatrix *= weight['ee_input']
if pConn['ee_input'] < 1.0:
weightMatrix, weightList = sparsenMatrix(weightMatrix, pConn['ee_input'])
else:
weightList = [(i, j, weightMatrix[i,j]) for j in xrange(nE) for i in xrange(nInput)]
np.save(dataPath+name, weightList)
print 'create connection matrices from E->I which are purely random'
connNameList = ['XeAi']
for name in connNameList:
weightMatrix = np.random.random((nInput, nI))
weightMatrix *= weight['ei_input']
weightMatrix, weightList = sparsenMatrix(weightMatrix, pConn['ei_input'])
print 'save connection matrix', name
np.save(dataPath+name, weightList)
print 'create connection matrices from E->I which are purely random'
connNameList = ['AeAi']
for name in connNameList:
if nE == nI:
weightList = [(i, i, weight['ei']) for i in xrange(nE)]
else:
weightMatrix = np.random.random((nE, nI))
weightMatrix *= weight['ei']
weightMatrix, weightList = sparsenMatrix(weightMatrix, pConn['ei'])
print 'save connection matrix', name
np.save(dataPath+name, weightList)
print 'create connection matrices from I->E which are purely random'
connNameList = ['AiAe']
for name in connNameList:
if nE == nI:
weightMatrix = np.ones((nI, nE))
weightMatrix *= weight['ie']
for i in xrange(nI):
weightMatrix[i,i] = 0
weightList = [(i, j, weightMatrix[i,j]) for i in xrange(nI) for j in xrange(nE)]
else:
weightMatrix = np.random.random((nI, nE))
weightMatrix *= weight['ie']
weightMatrix, weightList = sparsenMatrix(weightMatrix, pConn['ie'])
print 'save connection matrix', name
np.save(dataPath+name, weightList)
|
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https://github.com/peter-u-diehl/stdp-mnist/blob/d527ca3ee579d4f156d25ff160c0551a5ab82cf1/Diehl&Cook_MNIST_random_conn_generator.py#L37-L111
|
||||
matplotlib/trendvis
|
ec52af70d1ffba62edeeb15f4b6c181307ae2647
|
trendvis/xgrid_ystack.py
|
python
|
XGrid.reverse_xaxis
|
(self, reverse_x='all', adjust_bar_frame=True)
|
Reverse all or any x axis.
Parameters
----------
reverse_x : string or list of ints
Default 'all'. 'all' or list of indices of the x axes to be
reversed accepted. If unsure of index for a twin y axis in
``self.axes``, find using ``self.get_twin_rownum()``
adjust_bar_frame : Boolean
Default True. Realign ``matplotlib Rectangle patches``
made via ``self.draw_bar`` and ``self.draw_frame``.
|
Reverse all or any x axis.
|
[
"Reverse",
"all",
"or",
"any",
"x",
"axis",
"."
] |
def reverse_xaxis(self, reverse_x='all', adjust_bar_frame=True):
"""
Reverse all or any x axis.
Parameters
----------
reverse_x : string or list of ints
Default 'all'. 'all' or list of indices of the x axes to be
reversed accepted. If unsure of index for a twin y axis in
``self.axes``, find using ``self.get_twin_rownum()``
adjust_bar_frame : Boolean
Default True. Realign ``matplotlib Rectangle patches``
made via ``self.draw_bar`` and ``self.draw_frame``.
"""
if reverse_x is 'all':
reverse_x = range(0, self.mainax_dim)
# Invert x axis of each axis in first row
for r in reverse_x:
self.axes[0][r].invert_xaxis()
if adjust_bar_frame:
self.adjust_bar_frame()
|
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"[",
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"]",
".",
"invert_xaxis",
"(",
")",
"if",
"adjust_bar_frame",
":",
"self",
".",
"adjust_bar_frame",
"(",
")"
] |
https://github.com/matplotlib/trendvis/blob/ec52af70d1ffba62edeeb15f4b6c181307ae2647/trendvis/xgrid_ystack.py#L409-L433
|
||
dreadatour/Flake8Lint
|
8703c5633ac3fab4bd116da82aae7ff7bbc795c0
|
Flake8Lint.py
|
python
|
LintReport.get_gutter_mark
|
(self)
|
Return gutter mark icon or empty string if marks are disabled.
|
Return gutter mark icon or empty string if marks are disabled.
|
[
"Return",
"gutter",
"mark",
"icon",
"or",
"empty",
"string",
"if",
"marks",
"are",
"disabled",
"."
] |
def get_gutter_mark(self):
"""Return gutter mark icon or empty string if marks are disabled."""
# ST does not expect platform specific paths here, but only
# forward-slash separated paths relative to "Packages"
self.gutter_mark_success = '/'.join(
[settings.mark_themes_dir, 'success']
)
if int(sublime.version()) >= 3014:
self.gutter_mark_success += '.png'
self.gutter_mark = ''
mark_type = settings.gutter_marks
if mark_type in ('dot', 'circle', 'bookmark', 'cross'):
self.gutter_mark = mark_type
elif mark_type.startswith('theme-'):
theme = mark_type[6:]
if theme not in ('alpha', 'bright', 'dark', 'hard', 'simple'):
log("unknown gutter mark theme: '{0}'".format(mark_type))
return
# ST does not expect platform specific paths here, but only
# forward-slash separated paths relative to "Packages"
self.gutter_mark = '/'.join(
[settings.mark_themes_dir, '{0}-{{0}}'.format(theme)]
)
if int(sublime.version()) >= 3014:
self.gutter_mark += '.png'
|
[
"def",
"get_gutter_mark",
"(",
"self",
")",
":",
"# ST does not expect platform specific paths here, but only",
"# forward-slash separated paths relative to \"Packages\"",
"self",
".",
"gutter_mark_success",
"=",
"'/'",
".",
"join",
"(",
"[",
"settings",
".",
"mark_themes_dir",
",",
"'success'",
"]",
")",
"if",
"int",
"(",
"sublime",
".",
"version",
"(",
")",
")",
">=",
"3014",
":",
"self",
".",
"gutter_mark_success",
"+=",
"'.png'",
"self",
".",
"gutter_mark",
"=",
"''",
"mark_type",
"=",
"settings",
".",
"gutter_marks",
"if",
"mark_type",
"in",
"(",
"'dot'",
",",
"'circle'",
",",
"'bookmark'",
",",
"'cross'",
")",
":",
"self",
".",
"gutter_mark",
"=",
"mark_type",
"elif",
"mark_type",
".",
"startswith",
"(",
"'theme-'",
")",
":",
"theme",
"=",
"mark_type",
"[",
"6",
":",
"]",
"if",
"theme",
"not",
"in",
"(",
"'alpha'",
",",
"'bright'",
",",
"'dark'",
",",
"'hard'",
",",
"'simple'",
")",
":",
"log",
"(",
"\"unknown gutter mark theme: '{0}'\"",
".",
"format",
"(",
"mark_type",
")",
")",
"return",
"# ST does not expect platform specific paths here, but only",
"# forward-slash separated paths relative to \"Packages\"",
"self",
".",
"gutter_mark",
"=",
"'/'",
".",
"join",
"(",
"[",
"settings",
".",
"mark_themes_dir",
",",
"'{0}-{{0}}'",
".",
"format",
"(",
"theme",
")",
"]",
")",
"if",
"int",
"(",
"sublime",
".",
"version",
"(",
")",
")",
">=",
"3014",
":",
"self",
".",
"gutter_mark",
"+=",
"'.png'"
] |
https://github.com/dreadatour/Flake8Lint/blob/8703c5633ac3fab4bd116da82aae7ff7bbc795c0/Flake8Lint.py#L463-L490
|
||
omnilib/aiomultiprocess
|
3daaa8a22e129dec4298b2d3e4ff6fea742a8f3c
|
aiomultiprocess/core.py
|
python
|
Process.terminate
|
(self)
|
return self.aio_process.terminate()
|
Send SIGTERM to child process.
|
Send SIGTERM to child process.
|
[
"Send",
"SIGTERM",
"to",
"child",
"process",
"."
] |
def terminate(self) -> None:
"""Send SIGTERM to child process."""
return self.aio_process.terminate()
|
[
"def",
"terminate",
"(",
"self",
")",
"->",
"None",
":",
"return",
"self",
".",
"aio_process",
".",
"terminate",
"(",
")"
] |
https://github.com/omnilib/aiomultiprocess/blob/3daaa8a22e129dec4298b2d3e4ff6fea742a8f3c/aiomultiprocess/core.py#L195-L197
|
|
BYU-PCCL/holodeck
|
521c1c828f47abe7fc24b027fb907eaf26495aed
|
src/holodeck/packagemanager.py
|
python
|
get_scenario
|
(scenario_name)
|
return load_scenario_file(config_path)
|
Gets the scenario configuration associated with the given name
Args:
scenario_name (:obj:`str`): name of the configuration to load - eg "UrbanCity-Follow"
Must be an exact match. Name must be unique among all installed packages
Returns:
:obj:`dict`: A dictionary containing the configuration file
|
Gets the scenario configuration associated with the given name
|
[
"Gets",
"the",
"scenario",
"configuration",
"associated",
"with",
"the",
"given",
"name"
] |
def get_scenario(scenario_name):
"""Gets the scenario configuration associated with the given name
Args:
scenario_name (:obj:`str`): name of the configuration to load - eg "UrbanCity-Follow"
Must be an exact match. Name must be unique among all installed packages
Returns:
:obj:`dict`: A dictionary containing the configuration file
"""
config_path = _find_file_in_worlds_dir(scenario_name + ".json")
if config_path == "":
raise FileNotFoundError(
"The file `{file}.json` could not be found in {path}. "
"Make sure the package that contains {file} "
"is installed.".format(file=scenario_name, path=util.get_holodeck_path())
)
return load_scenario_file(config_path)
|
[
"def",
"get_scenario",
"(",
"scenario_name",
")",
":",
"config_path",
"=",
"_find_file_in_worlds_dir",
"(",
"scenario_name",
"+",
"\".json\"",
")",
"if",
"config_path",
"==",
"\"\"",
":",
"raise",
"FileNotFoundError",
"(",
"\"The file `{file}.json` could not be found in {path}. \"",
"\"Make sure the package that contains {file} \"",
"\"is installed.\"",
".",
"format",
"(",
"file",
"=",
"scenario_name",
",",
"path",
"=",
"util",
".",
"get_holodeck_path",
"(",
")",
")",
")",
"return",
"load_scenario_file",
"(",
"config_path",
")"
] |
https://github.com/BYU-PCCL/holodeck/blob/521c1c828f47abe7fc24b027fb907eaf26495aed/src/holodeck/packagemanager.py#L301-L321
|
|
zhaoolee/StarsAndClown
|
b2d4039cad2f9232b691e5976f787b49a0a2c113
|
node_modules/npmi/node_modules/npm/node_modules/node-gyp/gyp/pylib/gyp/input.py
|
python
|
GetIncludedBuildFiles
|
(build_file_path, aux_data, included=None)
|
return included
|
Return a list of all build files included into build_file_path.
The returned list will contain build_file_path as well as all other files
that it included, either directly or indirectly. Note that the list may
contain files that were included into a conditional section that evaluated
to false and was not merged into build_file_path's dict.
aux_data is a dict containing a key for each build file or included build
file. Those keys provide access to dicts whose "included" keys contain
lists of all other files included by the build file.
included should be left at its default None value by external callers. It
is used for recursion.
The returned list will not contain any duplicate entries. Each build file
in the list will be relative to the current directory.
|
Return a list of all build files included into build_file_path.
|
[
"Return",
"a",
"list",
"of",
"all",
"build",
"files",
"included",
"into",
"build_file_path",
"."
] |
def GetIncludedBuildFiles(build_file_path, aux_data, included=None):
"""Return a list of all build files included into build_file_path.
The returned list will contain build_file_path as well as all other files
that it included, either directly or indirectly. Note that the list may
contain files that were included into a conditional section that evaluated
to false and was not merged into build_file_path's dict.
aux_data is a dict containing a key for each build file or included build
file. Those keys provide access to dicts whose "included" keys contain
lists of all other files included by the build file.
included should be left at its default None value by external callers. It
is used for recursion.
The returned list will not contain any duplicate entries. Each build file
in the list will be relative to the current directory.
"""
if included == None:
included = []
if build_file_path in included:
return included
included.append(build_file_path)
for included_build_file in aux_data[build_file_path].get('included', []):
GetIncludedBuildFiles(included_build_file, aux_data, included)
return included
|
[
"def",
"GetIncludedBuildFiles",
"(",
"build_file_path",
",",
"aux_data",
",",
"included",
"=",
"None",
")",
":",
"if",
"included",
"==",
"None",
":",
"included",
"=",
"[",
"]",
"if",
"build_file_path",
"in",
"included",
":",
"return",
"included",
"included",
".",
"append",
"(",
"build_file_path",
")",
"for",
"included_build_file",
"in",
"aux_data",
"[",
"build_file_path",
"]",
".",
"get",
"(",
"'included'",
",",
"[",
"]",
")",
":",
"GetIncludedBuildFiles",
"(",
"included_build_file",
",",
"aux_data",
",",
"included",
")",
"return",
"included"
] |
https://github.com/zhaoolee/StarsAndClown/blob/b2d4039cad2f9232b691e5976f787b49a0a2c113/node_modules/npmi/node_modules/npm/node_modules/node-gyp/gyp/pylib/gyp/input.py#L143-L173
|
|
golismero/golismero
|
7d605b937e241f51c1ca4f47b20f755eeefb9d76
|
thirdparty_libs/openvas_lib/common.py
|
python
|
ConnectionManager._get_protocol_version
|
(self)
|
Get OMP protocol version. If host is 'dummy', return 'dummy' version.
:return: version of protocol
:rtype: str
:raises: ServerError, RemoteVersionError
|
Get OMP protocol version. If host is 'dummy', return 'dummy' version.
|
[
"Get",
"OMP",
"protocol",
"version",
".",
"If",
"host",
"is",
"dummy",
"return",
"dummy",
"version",
"."
] |
def _get_protocol_version(self):
"""
Get OMP protocol version. If host is 'dummy', return 'dummy' version.
:return: version of protocol
:rtype: str
:raises: ServerError, RemoteVersionError
"""
if self.__host == "dummy":
return "dummy"
response = self.make_xml_request('<get_version/>', xml_result=True)
v = response.find("version").text
if not v:
raise RemoteVersionError("Unknown remote server version")
else:
return v
|
[
"def",
"_get_protocol_version",
"(",
"self",
")",
":",
"if",
"self",
".",
"__host",
"==",
"\"dummy\"",
":",
"return",
"\"dummy\"",
"response",
"=",
"self",
".",
"make_xml_request",
"(",
"'<get_version/>'",
",",
"xml_result",
"=",
"True",
")",
"v",
"=",
"response",
".",
"find",
"(",
"\"version\"",
")",
".",
"text",
"if",
"not",
"v",
":",
"raise",
"RemoteVersionError",
"(",
"\"Unknown remote server version\"",
")",
"else",
":",
"return",
"v"
] |
https://github.com/golismero/golismero/blob/7d605b937e241f51c1ca4f47b20f755eeefb9d76/thirdparty_libs/openvas_lib/common.py#L233-L253
|
||
oilshell/oil
|
94388e7d44a9ad879b12615f6203b38596b5a2d3
|
opy/compiler2/transformer.py
|
python
|
Transformer.atom_lpar
|
(self, nodelist)
|
return self.com_node(nodelist[1])
|
[] |
def atom_lpar(self, nodelist):
if nodelist[1][0] == token.RPAR:
return Tuple((), lineno=nodelist[0][2])
return self.com_node(nodelist[1])
|
[
"def",
"atom_lpar",
"(",
"self",
",",
"nodelist",
")",
":",
"if",
"nodelist",
"[",
"1",
"]",
"[",
"0",
"]",
"==",
"token",
".",
"RPAR",
":",
"return",
"Tuple",
"(",
"(",
")",
",",
"lineno",
"=",
"nodelist",
"[",
"0",
"]",
"[",
"2",
"]",
")",
"return",
"self",
".",
"com_node",
"(",
"nodelist",
"[",
"1",
"]",
")"
] |
https://github.com/oilshell/oil/blob/94388e7d44a9ad879b12615f6203b38596b5a2d3/opy/compiler2/transformer.py#L825-L828
|
|||
python-discord/bot
|
26c5587ac13e5414361bb6e7ada42983b81014d2
|
bot/exts/info/python_news.py
|
python
|
PythonNews.start_tasks
|
(self)
|
Start the tasks for fetching new PEPs and mailing list messages.
|
Start the tasks for fetching new PEPs and mailing list messages.
|
[
"Start",
"the",
"tasks",
"for",
"fetching",
"new",
"PEPs",
"and",
"mailing",
"list",
"messages",
"."
] |
async def start_tasks(self) -> None:
"""Start the tasks for fetching new PEPs and mailing list messages."""
self.fetch_new_media.start()
|
[
"async",
"def",
"start_tasks",
"(",
"self",
")",
"->",
"None",
":",
"self",
".",
"fetch_new_media",
".",
"start",
"(",
")"
] |
https://github.com/python-discord/bot/blob/26c5587ac13e5414361bb6e7ada42983b81014d2/bot/exts/info/python_news.py#L48-L50
|
||
pandas-dev/pandas
|
5ba7d714014ae8feaccc0dd4a98890828cf2832d
|
pandas/io/clipboard/__init__.py
|
python
|
set_clipboard
|
(clipboard)
|
Explicitly sets the clipboard mechanism. The "clipboard mechanism" is how
the copy() and paste() functions interact with the operating system to
implement the copy/paste feature. The clipboard parameter must be one of:
- pbcopy
- pbobjc (default on Mac OS X)
- qt
- xclip
- xsel
- klipper
- windows (default on Windows)
- no (this is what is set when no clipboard mechanism can be found)
|
Explicitly sets the clipboard mechanism. The "clipboard mechanism" is how
the copy() and paste() functions interact with the operating system to
implement the copy/paste feature. The clipboard parameter must be one of:
- pbcopy
- pbobjc (default on Mac OS X)
- qt
- xclip
- xsel
- klipper
- windows (default on Windows)
- no (this is what is set when no clipboard mechanism can be found)
|
[
"Explicitly",
"sets",
"the",
"clipboard",
"mechanism",
".",
"The",
"clipboard",
"mechanism",
"is",
"how",
"the",
"copy",
"()",
"and",
"paste",
"()",
"functions",
"interact",
"with",
"the",
"operating",
"system",
"to",
"implement",
"the",
"copy",
"/",
"paste",
"feature",
".",
"The",
"clipboard",
"parameter",
"must",
"be",
"one",
"of",
":",
"-",
"pbcopy",
"-",
"pbobjc",
"(",
"default",
"on",
"Mac",
"OS",
"X",
")",
"-",
"qt",
"-",
"xclip",
"-",
"xsel",
"-",
"klipper",
"-",
"windows",
"(",
"default",
"on",
"Windows",
")",
"-",
"no",
"(",
"this",
"is",
"what",
"is",
"set",
"when",
"no",
"clipboard",
"mechanism",
"can",
"be",
"found",
")"
] |
def set_clipboard(clipboard):
"""
Explicitly sets the clipboard mechanism. The "clipboard mechanism" is how
the copy() and paste() functions interact with the operating system to
implement the copy/paste feature. The clipboard parameter must be one of:
- pbcopy
- pbobjc (default on Mac OS X)
- qt
- xclip
- xsel
- klipper
- windows (default on Windows)
- no (this is what is set when no clipboard mechanism can be found)
"""
global copy, paste
clipboard_types = {
"pbcopy": init_osx_pbcopy_clipboard,
"pyobjc": init_osx_pyobjc_clipboard,
"qt": init_qt_clipboard, # TODO - split this into 'qtpy', 'pyqt4', and 'pyqt5'
"xclip": init_xclip_clipboard,
"xsel": init_xsel_clipboard,
"klipper": init_klipper_clipboard,
"windows": init_windows_clipboard,
"no": init_no_clipboard,
}
if clipboard not in clipboard_types:
allowed_clipboard_types = [repr(_) for _ in clipboard_types.keys()]
raise ValueError(
f"Argument must be one of {', '.join(allowed_clipboard_types)}"
)
# Sets pyperclip's copy() and paste() functions:
copy, paste = clipboard_types[clipboard]()
|
[
"def",
"set_clipboard",
"(",
"clipboard",
")",
":",
"global",
"copy",
",",
"paste",
"clipboard_types",
"=",
"{",
"\"pbcopy\"",
":",
"init_osx_pbcopy_clipboard",
",",
"\"pyobjc\"",
":",
"init_osx_pyobjc_clipboard",
",",
"\"qt\"",
":",
"init_qt_clipboard",
",",
"# TODO - split this into 'qtpy', 'pyqt4', and 'pyqt5'",
"\"xclip\"",
":",
"init_xclip_clipboard",
",",
"\"xsel\"",
":",
"init_xsel_clipboard",
",",
"\"klipper\"",
":",
"init_klipper_clipboard",
",",
"\"windows\"",
":",
"init_windows_clipboard",
",",
"\"no\"",
":",
"init_no_clipboard",
",",
"}",
"if",
"clipboard",
"not",
"in",
"clipboard_types",
":",
"allowed_clipboard_types",
"=",
"[",
"repr",
"(",
"_",
")",
"for",
"_",
"in",
"clipboard_types",
".",
"keys",
"(",
")",
"]",
"raise",
"ValueError",
"(",
"f\"Argument must be one of {', '.join(allowed_clipboard_types)}\"",
")",
"# Sets pyperclip's copy() and paste() functions:",
"copy",
",",
"paste",
"=",
"clipboard_types",
"[",
"clipboard",
"]",
"(",
")"
] |
https://github.com/pandas-dev/pandas/blob/5ba7d714014ae8feaccc0dd4a98890828cf2832d/pandas/io/clipboard/__init__.py#L581-L615
|
||
facebookresearch/ReAgent
|
52f666670a7fa03206812ef48949f6b934d400f7
|
reagent/samplers/frechet.py
|
python
|
FrechetSort.log_prob
|
(
self,
scores: torch.Tensor,
action: torch.Tensor,
equiv_len_override: Optional[torch.Tensor] = None,
)
|
return log_prob
|
What is the probability of a given set of scores producing the given
list of permutations only considering the top `equiv_len` ranks?
We may want to override the default equiv_len here when we know the having larger
action space doesn't matter. i.e. in Reels
|
What is the probability of a given set of scores producing the given
list of permutations only considering the top `equiv_len` ranks?
|
[
"What",
"is",
"the",
"probability",
"of",
"a",
"given",
"set",
"of",
"scores",
"producing",
"the",
"given",
"list",
"of",
"permutations",
"only",
"considering",
"the",
"top",
"equiv_len",
"ranks?"
] |
def log_prob(
self,
scores: torch.Tensor,
action: torch.Tensor,
equiv_len_override: Optional[torch.Tensor] = None,
) -> torch.Tensor:
"""
What is the probability of a given set of scores producing the given
list of permutations only considering the top `equiv_len` ranks?
We may want to override the default equiv_len here when we know the having larger
action space doesn't matter. i.e. in Reels
"""
upto = self.upto
if equiv_len_override is not None:
assert equiv_len_override.shape == (
scores.shape[0],
), f"Invalid shape {equiv_len_override.shape}, compared to scores {scores.shape}. equiv_len_override {equiv_len_override}"
upto = equiv_len_override.long()
if self.topk is not None and torch.any(equiv_len_override > self.topk):
raise ValueError(
f"Override {equiv_len_override} cannot exceed topk={self.topk}."
)
squeeze = False
if len(scores.shape) == 1:
squeeze = True
scores = scores.unsqueeze(0)
action = action.unsqueeze(0)
assert len(action.shape) == len(scores.shape) == 2, "scores should be batch"
if action.shape[1] > scores.shape[1]:
raise ValueError(
f"action cardinality ({action.shape[1]}) is larger than the number of scores ({scores.shape[1]})"
)
elif action.shape[1] < scores.shape[1]:
raise NotImplementedError(
f"This semantic is ambiguous. If you have shorter slate, pad it with scores.shape[1] ({scores.shape[1]})"
)
log_scores = scores if self.log_scores else torch.log(scores)
n = log_scores.shape[-1]
# Add scores for the padding value
log_scores = torch.cat(
[
log_scores,
torch.full(
(log_scores.shape[0], 1), -math.inf, device=log_scores.device
),
],
dim=1,
)
log_scores = torch.gather(log_scores, 1, action) * self.shape
p = upto if upto is not None else n
# We should unsqueeze here
if isinstance(p, int):
log_prob = sum(
torch.nan_to_num(
F.log_softmax(log_scores[:, i:], dim=1)[:, 0], neginf=0.0
)
for i in range(p)
)
elif isinstance(p, torch.Tensor):
# do masked sum
log_prob = sum(
torch.nan_to_num(
F.log_softmax(log_scores[:, i:], dim=1)[:, 0], neginf=0.0
)
* (i < p).float()
for i in range(n)
)
else:
raise RuntimeError(f"p is {p}")
assert not torch.any(log_prob.isnan()), f"Nan in {log_prob}"
return log_prob
|
[
"def",
"log_prob",
"(",
"self",
",",
"scores",
":",
"torch",
".",
"Tensor",
",",
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":",
"torch",
".",
"Tensor",
",",
"equiv_len_override",
":",
"Optional",
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"torch",
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"=",
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",",
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"]",
",",
")",
",",
"f\"Invalid shape {equiv_len_override.shape}, compared to scores {scores.shape}. equiv_len_override {equiv_len_override}\"",
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"f\"Override {equiv_len_override} cannot exceed topk={self.topk}.\"",
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"shape",
"[",
"1",
"]",
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"f\"action cardinality ({action.shape[1]}) is larger than the number of scores ({scores.shape[1]})\"",
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"[",
"1",
"]",
"<",
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"shape",
"[",
"1",
"]",
":",
"raise",
"NotImplementedError",
"(",
"f\"This semantic is ambiguous. If you have shorter slate, pad it with scores.shape[1] ({scores.shape[1]})\"",
")",
"log_scores",
"=",
"scores",
"if",
"self",
".",
"log_scores",
"else",
"torch",
".",
"log",
"(",
"scores",
")",
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"=",
"log_scores",
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"-",
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"# Add scores for the padding value",
"log_scores",
"=",
"torch",
".",
"cat",
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"[",
"log_scores",
",",
"torch",
".",
"full",
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"log_scores",
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",",
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")",
",",
"-",
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",",
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"device",
")",
",",
"]",
",",
"dim",
"=",
"1",
",",
")",
"log_scores",
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"gather",
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"log_scores",
",",
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",",
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"# We should unsqueeze here",
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"log_softmax",
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"(",
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"i",
"in",
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"(",
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")",
")",
"else",
":",
"raise",
"RuntimeError",
"(",
"f\"p is {p}\"",
")",
"assert",
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"torch",
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"any",
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"log_prob",
".",
"isnan",
"(",
")",
")",
",",
"f\"Nan in {log_prob}\"",
"return",
"log_prob"
] |
https://github.com/facebookresearch/ReAgent/blob/52f666670a7fa03206812ef48949f6b934d400f7/reagent/samplers/frechet.py#L85-L161
|
|
IronLanguages/main
|
a949455434b1fda8c783289e897e78a9a0caabb5
|
External.LCA_RESTRICTED/Languages/IronPython/27/Lib/site-packages/win32/scripts/regsetup.py
|
python
|
FindRegisterPackage
|
(packageName, knownFile, searchPaths, registryAppName = None)
|
Find and Register a package.
Assumes the core registry setup correctly.
In addition, if the location located by the package is already
in the **core** path, then an entry is registered, but no path.
(no other paths are checked, as the application whose path was used
may later be uninstalled. This should not happen with the core)
|
Find and Register a package.
|
[
"Find",
"and",
"Register",
"a",
"package",
"."
] |
def FindRegisterPackage(packageName, knownFile, searchPaths, registryAppName = None):
"""Find and Register a package.
Assumes the core registry setup correctly.
In addition, if the location located by the package is already
in the **core** path, then an entry is registered, but no path.
(no other paths are checked, as the application whose path was used
may later be uninstalled. This should not happen with the core)
"""
import regutil, string
if not packageName: raise error("A package name must be supplied")
corePaths = regutil.GetRegisteredNamedPath(None).split(";")
if not searchPaths: searchPaths = corePaths
registryAppName = registryAppName or packageName
try:
pathLook, pathAdd = FindPackagePath(packageName, knownFile, searchPaths)
if pathAdd is not None:
if pathAdd in corePaths:
pathAdd = ""
regutil.RegisterNamedPath(registryAppName, pathAdd)
return pathLook
except error, details:
print "*** The %s package could not be registered - %s" % (packageName, details)
print "*** Please ensure you have passed the correct paths on the command line."
print "*** - For packages, you should pass a path to the packages parent directory,"
print "*** - and not the package directory itself..."
|
[
"def",
"FindRegisterPackage",
"(",
"packageName",
",",
"knownFile",
",",
"searchPaths",
",",
"registryAppName",
"=",
"None",
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"import",
"regutil",
",",
"string",
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"\"A package name must be supplied\"",
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",",
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"\"*** The %s package could not be registered - %s\"",
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",",
"details",
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"\"*** Please ensure you have passed the correct paths on the command line.\"",
"print",
"\"*** - For packages, you should pass a path to the packages parent directory,\"",
"print",
"\"*** - and not the package directory itself...\""
] |
https://github.com/IronLanguages/main/blob/a949455434b1fda8c783289e897e78a9a0caabb5/External.LCA_RESTRICTED/Languages/IronPython/27/Lib/site-packages/win32/scripts/regsetup.py#L236-L262
|
||
Azure/azure-devops-cli-extension
|
11334cd55806bef0b99c3bee5a438eed71e44037
|
azure-devops/azext_devops/devops_sdk/v5_1/core/core_client.py
|
python
|
CoreClient.get_project_properties
|
(self, project_id, keys=None)
|
return self._deserialize('[ProjectProperty]', self._unwrap_collection(response))
|
GetProjectProperties.
[Preview API] Get a collection of team project properties.
:param str project_id: The team project ID.
:param [str] keys: A comma-delimited string of team project property names. Wildcard characters ("?" and "*") are supported. If no key is specified, all properties will be returned.
:rtype: [ProjectProperty]
|
GetProjectProperties.
[Preview API] Get a collection of team project properties.
:param str project_id: The team project ID.
:param [str] keys: A comma-delimited string of team project property names. Wildcard characters ("?" and "*") are supported. If no key is specified, all properties will be returned.
:rtype: [ProjectProperty]
|
[
"GetProjectProperties",
".",
"[",
"Preview",
"API",
"]",
"Get",
"a",
"collection",
"of",
"team",
"project",
"properties",
".",
":",
"param",
"str",
"project_id",
":",
"The",
"team",
"project",
"ID",
".",
":",
"param",
"[",
"str",
"]",
"keys",
":",
"A",
"comma",
"-",
"delimited",
"string",
"of",
"team",
"project",
"property",
"names",
".",
"Wildcard",
"characters",
"(",
"?",
"and",
"*",
")",
"are",
"supported",
".",
"If",
"no",
"key",
"is",
"specified",
"all",
"properties",
"will",
"be",
"returned",
".",
":",
"rtype",
":",
"[",
"ProjectProperty",
"]"
] |
def get_project_properties(self, project_id, keys=None):
"""GetProjectProperties.
[Preview API] Get a collection of team project properties.
:param str project_id: The team project ID.
:param [str] keys: A comma-delimited string of team project property names. Wildcard characters ("?" and "*") are supported. If no key is specified, all properties will be returned.
:rtype: [ProjectProperty]
"""
route_values = {}
if project_id is not None:
route_values['projectId'] = self._serialize.url('project_id', project_id, 'str')
query_parameters = {}
if keys is not None:
keys = ",".join(keys)
query_parameters['keys'] = self._serialize.query('keys', keys, 'str')
response = self._send(http_method='GET',
location_id='4976a71a-4487-49aa-8aab-a1eda469037a',
version='5.1-preview.1',
route_values=route_values,
query_parameters=query_parameters)
return self._deserialize('[ProjectProperty]', self._unwrap_collection(response))
|
[
"def",
"get_project_properties",
"(",
"self",
",",
"project_id",
",",
"keys",
"=",
"None",
")",
":",
"route_values",
"=",
"{",
"}",
"if",
"project_id",
"is",
"not",
"None",
":",
"route_values",
"[",
"'projectId'",
"]",
"=",
"self",
".",
"_serialize",
".",
"url",
"(",
"'project_id'",
",",
"project_id",
",",
"'str'",
")",
"query_parameters",
"=",
"{",
"}",
"if",
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"\",\"",
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"'keys'",
",",
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",",
"'str'",
")",
"response",
"=",
"self",
".",
"_send",
"(",
"http_method",
"=",
"'GET'",
",",
"location_id",
"=",
"'4976a71a-4487-49aa-8aab-a1eda469037a'",
",",
"version",
"=",
"'5.1-preview.1'",
",",
"route_values",
"=",
"route_values",
",",
"query_parameters",
"=",
"query_parameters",
")",
"return",
"self",
".",
"_deserialize",
"(",
"'[ProjectProperty]'",
",",
"self",
".",
"_unwrap_collection",
"(",
"response",
")",
")"
] |
https://github.com/Azure/azure-devops-cli-extension/blob/11334cd55806bef0b99c3bee5a438eed71e44037/azure-devops/azext_devops/devops_sdk/v5_1/core/core_client.py#L308-L327
|
|
pyglet/pyglet
|
2833c1df902ca81aeeffa786c12e7e87d402434b
|
pyglet/canvas/base.py
|
python
|
Canvas.__init__
|
(self, display)
|
:parameters:
`display` : `Display`
:attr:`display`
|
:parameters:
`display` : `Display`
:attr:`display`
|
[
":",
"parameters",
":",
"display",
":",
"Display",
":",
"attr",
":",
"display"
] |
def __init__(self, display):
"""
:parameters:
`display` : `Display`
:attr:`display`
"""
self.display = display
"""Display this canvas was created on."""
|
[
"def",
"__init__",
"(",
"self",
",",
"display",
")",
":",
"self",
".",
"display",
"=",
"display",
"\"\"\"Display this canvas was created on.\"\"\""
] |
https://github.com/pyglet/pyglet/blob/2833c1df902ca81aeeffa786c12e7e87d402434b/pyglet/canvas/base.py#L357-L366
|
||
gkrizek/bash-lambda-layer
|
703b0ade8174022d44779d823172ab7ac33a5505
|
bin/botocore/httpsession.py
|
python
|
ProxyConfiguration.proxy_url_for
|
(self, url)
|
return proxy
|
Retrirves the corresponding proxy url for a given url.
|
Retrirves the corresponding proxy url for a given url.
|
[
"Retrirves",
"the",
"corresponding",
"proxy",
"url",
"for",
"a",
"given",
"url",
"."
] |
def proxy_url_for(self, url):
"""Retrirves the corresponding proxy url for a given url. """
parsed_url = urlparse(url)
proxy = self._proxies.get(parsed_url.scheme)
if proxy:
proxy = self._fix_proxy_url(proxy)
return proxy
|
[
"def",
"proxy_url_for",
"(",
"self",
",",
"url",
")",
":",
"parsed_url",
"=",
"urlparse",
"(",
"url",
")",
"proxy",
"=",
"self",
".",
"_proxies",
".",
"get",
"(",
"parsed_url",
".",
"scheme",
")",
"if",
"proxy",
":",
"proxy",
"=",
"self",
".",
"_fix_proxy_url",
"(",
"proxy",
")",
"return",
"proxy"
] |
https://github.com/gkrizek/bash-lambda-layer/blob/703b0ade8174022d44779d823172ab7ac33a5505/bin/botocore/httpsession.py#L98-L104
|
|
Abjad/abjad
|
d0646dfbe83db3dc5ab268f76a0950712b87b7fd
|
abjad/contextmanagers.py
|
python
|
RedirectedStreams.__enter__
|
(self)
|
return self
|
Enters redirected streams context manager.
Returns none.
|
Enters redirected streams context manager.
|
[
"Enters",
"redirected",
"streams",
"context",
"manager",
"."
] |
def __enter__(self):
"""
Enters redirected streams context manager.
Returns none.
"""
self._old_stdout, self._old_stderr = sys.stdout, sys.stderr
self._old_stdout.flush()
self._old_stderr.flush()
sys.stdout, sys.stderr = self._stdout, self._stderr
return self
|
[
"def",
"__enter__",
"(",
"self",
")",
":",
"self",
".",
"_old_stdout",
",",
"self",
".",
"_old_stderr",
"=",
"sys",
".",
"stdout",
",",
"sys",
".",
"stderr",
"self",
".",
"_old_stdout",
".",
"flush",
"(",
")",
"self",
".",
"_old_stderr",
".",
"flush",
"(",
")",
"sys",
".",
"stdout",
",",
"sys",
".",
"stderr",
"=",
"self",
".",
"_stdout",
",",
"self",
".",
"_stderr",
"return",
"self"
] |
https://github.com/Abjad/abjad/blob/d0646dfbe83db3dc5ab268f76a0950712b87b7fd/abjad/contextmanagers.py#L472-L482
|
|
rail-berkeley/rlkit
|
c81509d982b4d52a6239e7bfe7d2540e3d3cd986
|
rlkit/torch/smac/smac.py
|
python
|
SmacTrainer.train_from_torch
|
(self, batch)
|
Policy and Alpha Loss
|
Policy and Alpha Loss
|
[
"Policy",
"and",
"Alpha",
"Loss"
] |
def train_from_torch(self, batch):
rewards = batch['rewards']
terminals = batch['terminals']
obs = batch['observations']
actions = batch['actions']
next_obs = batch['next_observations']
context = batch['context']
if self.reward_transform:
rewards = self.reward_transform(rewards)
if self.terminal_transform:
terminals = self.terminal_transform(terminals)
"""
Policy and Alpha Loss
"""
dist, p_z, task_z_with_grad = self.agent(
obs, context, return_latent_posterior_and_task_z=True,
)
task_z_detached = task_z_with_grad.detach()
new_obs_actions, log_pi = dist.rsample_and_logprob()
log_pi = log_pi.unsqueeze(1)
next_dist = self.agent(next_obs, context)
if self._debug_ignore_context:
task_z_with_grad = task_z_with_grad * 0
# flattens out the task dimension
t, b, _ = obs.size()
obs = obs.view(t * b, -1)
actions = actions.view(t * b, -1)
next_obs = next_obs.view(t * b, -1)
unscaled_rewards_flat = rewards.view(t * b, 1)
rewards_flat = unscaled_rewards_flat * self.reward_scale
terms_flat = terminals.view(t * b, 1)
if self.use_automatic_entropy_tuning:
alpha_loss = -(self.log_alpha * (
log_pi + self.target_entropy).detach()).mean()
self.alpha_optimizer.zero_grad()
alpha_loss.backward()
self.alpha_optimizer.step()
alpha = self.log_alpha.exp()
else:
alpha_loss = 0
alpha = self.alpha
"""
QF Loss
"""
if self.backprop_q_loss_into_encoder:
q1_pred = self.qf1(obs, actions, task_z_with_grad)
q2_pred = self.qf2(obs, actions, task_z_with_grad)
else:
q1_pred = self.qf1(obs, actions, task_z_detached)
q2_pred = self.qf2(obs, actions, task_z_detached)
# Make sure policy accounts for squashing functions like tanh correctly!
new_next_actions, new_log_pi = next_dist.rsample_and_logprob()
new_log_pi = new_log_pi.unsqueeze(1)
with torch.no_grad():
target_q_values = torch.min(
self.target_qf1(next_obs, new_next_actions, task_z_detached),
self.target_qf2(next_obs, new_next_actions, task_z_detached),
) - alpha * new_log_pi
q_target = rewards_flat + (
1. - terms_flat) * self.discount * target_q_values
qf1_loss = self.qf_criterion(q1_pred, q_target.detach())
qf2_loss = self.qf_criterion(q2_pred, q_target.detach())
"""
Context Encoder Loss
"""
if self._debug_use_ground_truth_context:
kl_div = kl_loss = ptu.zeros(0)
else:
kl_div = kl_divergence(p_z, self.agent.latent_prior).mean(dim=0).sum()
kl_loss = self.kl_lambda * kl_div
if self.train_context_decoder:
# TODO: change to use a distribution
reward_pred = self.context_decoder(obs, actions, task_z_with_grad)
reward_prediction_loss = ((reward_pred - unscaled_rewards_flat)**2).mean()
context_loss = kl_loss + reward_prediction_loss
else:
context_loss = kl_loss
reward_prediction_loss = ptu.zeros(1)
"""
Policy Loss
"""
qf1_new_actions = self.qf1(obs, new_obs_actions, task_z_detached)
qf2_new_actions = self.qf2(obs, new_obs_actions, task_z_detached)
q_new_actions = torch.min(
qf1_new_actions,
qf2_new_actions,
)
# Advantage-weighted regression
if self.vf_K > 1:
vs = []
for i in range(self.vf_K):
u = dist.sample()
q1 = self.qf1(obs, u, task_z_detached)
q2 = self.qf2(obs, u, task_z_detached)
v = torch.min(q1, q2)
# v = q1
vs.append(v)
v_pi = torch.cat(vs, 1).mean(dim=1)
else:
# v_pi = self.qf1(obs, new_obs_actions)
v1_pi = self.qf1(obs, new_obs_actions, task_z_detached)
v2_pi = self.qf2(obs, new_obs_actions, task_z_detached)
v_pi = torch.min(v1_pi, v2_pi)
u = actions
if self.awr_min_q:
q_adv = torch.min(q1_pred, q2_pred)
else:
q_adv = q1_pred
policy_logpp = dist.log_prob(u)
if self.use_automatic_beta_tuning:
buffer_dist = self.buffer_policy(obs)
beta = self.log_beta.exp()
kldiv = torch.distributions.kl.kl_divergence(dist, buffer_dist)
beta_loss = -1 * (
beta * (kldiv - self.beta_epsilon).detach()).mean()
self.beta_optimizer.zero_grad()
beta_loss.backward()
self.beta_optimizer.step()
else:
beta = self.beta_schedule.get_value(self._n_train_steps_total)
beta_loss = ptu.zeros(1)
score = q_adv - v_pi
if self.mask_positive_advantage:
score = torch.sign(score)
if self.clip_score is not None:
score = torch.clamp(score, max=self.clip_score)
weights = batch.get('weights', None)
if self.weight_loss and weights is None:
if self.normalize_over_batch == True:
weights = F.softmax(score / beta, dim=0)
elif self.normalize_over_batch == "whiten":
adv_mean = torch.mean(score)
adv_std = torch.std(score) + 1e-5
normalized_score = (score - adv_mean) / adv_std
weights = torch.exp(normalized_score / beta)
elif self.normalize_over_batch == "exp":
weights = torch.exp(score / beta)
elif self.normalize_over_batch == "step_fn":
weights = (score > 0).float()
elif self.normalize_over_batch == False:
weights = score
elif self.normalize_over_batch == 'uniform':
weights = F.softmax(ptu.ones_like(score) / beta, dim=0)
else:
raise ValueError(self.normalize_over_batch)
weights = weights[:, 0]
policy_loss = alpha * log_pi.mean()
if self.use_awr_update and self.weight_loss:
policy_loss = policy_loss + self.awr_weight * (
-policy_logpp * len(weights) * weights.detach()).mean()
elif self.use_awr_update:
policy_loss = policy_loss + self.awr_weight * (-policy_logpp).mean()
if self.use_reparam_update:
policy_loss = policy_loss + self.train_reparam_weight * (
-q_new_actions).mean()
policy_loss = self.rl_weight * policy_loss
"""
Update networks
"""
if self._n_train_steps_total % self.q_update_period == 0:
if self.train_encoder_decoder:
self.context_optimizer.zero_grad()
if self.train_agent:
self.qf1_optimizer.zero_grad()
self.qf2_optimizer.zero_grad()
context_loss.backward(retain_graph=True)
# retain graph because the encoder is trained by both QF losses
qf1_loss.backward(retain_graph=True)
qf2_loss.backward()
if self.train_agent:
self.qf1_optimizer.step()
self.qf2_optimizer.step()
if self.train_encoder_decoder:
self.context_optimizer.step()
if self.train_agent:
if self._n_train_steps_total % self.policy_update_period == 0 and self.update_policy:
self.policy_optimizer.zero_grad()
policy_loss.backward()
self.policy_optimizer.step()
self._num_gradient_steps += 1
"""
Soft Updates
"""
if self._n_train_steps_total % self.target_update_period == 0:
ptu.soft_update_from_to(
self.qf1, self.target_qf1, self.soft_target_tau
)
ptu.soft_update_from_to(
self.qf2, self.target_qf2, self.soft_target_tau
)
"""
Save some statistics for eval
"""
if self._need_to_update_eval_statistics:
self._need_to_update_eval_statistics = False
"""
Eval should set this to None.
This way, these statistics are only computed for one batch.
"""
policy_loss = (log_pi - q_new_actions).mean()
self.eval_statistics['QF1 Loss'] = np.mean(ptu.get_numpy(qf1_loss))
self.eval_statistics['QF2 Loss'] = np.mean(ptu.get_numpy(qf2_loss))
self.eval_statistics['Policy Loss'] = np.mean(ptu.get_numpy(
policy_loss
))
self.eval_statistics.update(create_stats_ordered_dict(
'Q1 Predictions',
ptu.get_numpy(q1_pred),
))
self.eval_statistics.update(create_stats_ordered_dict(
'Q2 Predictions',
ptu.get_numpy(q2_pred),
))
self.eval_statistics.update(create_stats_ordered_dict(
'Q Targets',
ptu.get_numpy(q_target),
))
self.eval_statistics['task_embedding/kl_divergence'] = (
ptu.get_numpy(kl_div)
)
self.eval_statistics['task_embedding/kl_loss'] = (
ptu.get_numpy(kl_loss)
)
self.eval_statistics['task_embedding/reward_prediction_loss'] = (
ptu.get_numpy(reward_prediction_loss)
)
self.eval_statistics['task_embedding/context_loss'] = (
ptu.get_numpy(context_loss)
)
self.eval_statistics.update(create_stats_ordered_dict(
'Log Pis',
ptu.get_numpy(log_pi),
))
self.eval_statistics.update(create_stats_ordered_dict(
'rewards',
ptu.get_numpy(rewards),
))
self.eval_statistics.update(create_stats_ordered_dict(
'terminals',
ptu.get_numpy(terminals),
))
policy_statistics = add_prefix(dist.get_diagnostics(), "policy/")
self.eval_statistics.update(policy_statistics)
self.eval_statistics.update(create_stats_ordered_dict(
'Advantage Weights',
ptu.get_numpy(weights),
))
self.eval_statistics.update(create_stats_ordered_dict(
'Advantage Score',
ptu.get_numpy(score),
))
self.eval_statistics['reparam_weight'] = self.train_reparam_weight
self.eval_statistics['num_gradient_steps'] = (
self._num_gradient_steps
)
if self.use_automatic_entropy_tuning:
self.eval_statistics['Alpha'] = alpha.item()
self.eval_statistics['Alpha Loss'] = alpha_loss.item()
if self.use_automatic_beta_tuning:
self.eval_statistics.update({
"adaptive_beta/beta": ptu.get_numpy(beta.mean()),
"adaptive_beta/beta loss": ptu.get_numpy(beta_loss.mean()),
})
self._n_train_steps_total += 1
|
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https://github.com/rail-berkeley/rlkit/blob/c81509d982b4d52a6239e7bfe7d2540e3d3cd986/rlkit/torch/smac/smac.py#L324-L617
|
||
mesalock-linux/mesapy
|
ed546d59a21b36feb93e2309d5c6b75aa0ad95c9
|
lib-python/2.7/string.py
|
python
|
capwords
|
(s, sep=None)
|
return (sep or ' ').join(x.capitalize() for x in s.split(sep))
|
capwords(s [,sep]) -> string
Split the argument into words using split, capitalize each
word using capitalize, and join the capitalized words using
join. If the optional second argument sep is absent or None,
runs of whitespace characters are replaced by a single space
and leading and trailing whitespace are removed, otherwise
sep is used to split and join the words.
|
capwords(s [,sep]) -> string
|
[
"capwords",
"(",
"s",
"[",
"sep",
"]",
")",
"-",
">",
"string"
] |
def capwords(s, sep=None):
"""capwords(s [,sep]) -> string
Split the argument into words using split, capitalize each
word using capitalize, and join the capitalized words using
join. If the optional second argument sep is absent or None,
runs of whitespace characters are replaced by a single space
and leading and trailing whitespace are removed, otherwise
sep is used to split and join the words.
"""
return (sep or ' ').join(x.capitalize() for x in s.split(sep))
|
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https://github.com/mesalock-linux/mesapy/blob/ed546d59a21b36feb93e2309d5c6b75aa0ad95c9/lib-python/2.7/string.py#L45-L56
|
|
beched/libpywebhack
|
40dd01a68956d35e7a7b6b811b69ef0f688645c6
|
libpywebhack.py
|
python
|
WebHack.dobrute
|
(self, a, b)
|
A worker-method for WebHack.brutesubs()
:param a: beginning of interval
:param b: end of interval
|
A worker-method for WebHack.brutesubs()
:param a: beginning of interval
:param b: end of interval
|
[
"A",
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"-",
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":",
"param",
"b",
":",
"end",
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] |
def dobrute(self, a, b):
"""
A worker-method for WebHack.brutesubs()
:param a: beginning of interval
:param b: end of interval
"""
for sub in self.subs[a: b]:
if self.checked_subs % 1000 == 0 and self.checked_subs != 0:
self.rep_log('%s names proceeded' % self.checked_subs)
try:
conn = httplib.HTTPConnection('%s.%s' % (sub, self.host), timeout=5)
if self.ban_regex != '':
conn.request('GET', '/')
else:
conn.request('HEAD', '/')
res = conn.getresponse()
self.cnt_reqs += 1
if (str(res.status) not in self.ban_codes) and not (
self.ban_regex != None and re.search(self.ban_regex, res.read())):
domain = '%s.%s' % (sub, self.host)
self.known_subs.append(domain)
self.rep_log('Found: %s' % domain)
conn.close()
except (socket.gaierror, socket.herror):
pass
except (socket.timeout, socket.error):
self.rep_log('Found: %s.%s' % (sub, self.host))
self.checked_subs += 1
|
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] |
https://github.com/beched/libpywebhack/blob/40dd01a68956d35e7a7b6b811b69ef0f688645c6/libpywebhack.py#L438-L465
|
||
facelessuser/pymdown-extensions
|
7a9d548ed3aa921e77fbedd202947ba884cca04c
|
pymdownx/b64.py
|
python
|
B64Extension.__init__
|
(self, *args, **kwargs)
|
Initialize.
|
Initialize.
|
[
"Initialize",
"."
] |
def __init__(self, *args, **kwargs):
"""Initialize."""
self.config = {
'base_path': [".", "Base path for b64 to use to resolve paths - Default: \".\""]
}
super(B64Extension, self).__init__(*args, **kwargs)
|
[
"def",
"__init__",
"(",
"self",
",",
"*",
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",",
"*",
"*",
"kwargs",
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":",
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"config",
"=",
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"'base_path'",
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"\".\"",
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https://github.com/facelessuser/pymdown-extensions/blob/7a9d548ed3aa921e77fbedd202947ba884cca04c/pymdownx/b64.py#L124-L131
|
||
aws/aws-sam-cli
|
2aa7bf01b2e0b0864ef63b1898a8b30577443acc
|
samcli/lib/sync/flows/layer_sync_flow.py
|
python
|
AbstractLayerSyncFlow._get_latest_layer_version
|
(self)
|
return layer_versions[0].get("Version")
|
Fetches all layer versions from remote and returns the latest one
|
Fetches all layer versions from remote and returns the latest one
|
[
"Fetches",
"all",
"layer",
"versions",
"from",
"remote",
"and",
"returns",
"the",
"latest",
"one"
] |
def _get_latest_layer_version(self):
"""Fetches all layer versions from remote and returns the latest one"""
layer_versions = self._lambda_client.list_layer_versions(LayerName=self._layer_arn).get("LayerVersions", [])
if not layer_versions:
raise NoLayerVersionsFoundError(self._layer_arn)
return layer_versions[0].get("Version")
|
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https://github.com/aws/aws-sam-cli/blob/2aa7bf01b2e0b0864ef63b1898a8b30577443acc/samcli/lib/sync/flows/layer_sync_flow.py#L76-L81
|
|
MeanEYE/Sunflower
|
1024bbdde3b8e202ddad3553b321a7b6230bffc9
|
sunflower/gui/operation_dialog.py
|
python
|
OperationDialog.increment_current_count
|
(self, value)
|
Increment current file count by value
|
Increment current file count by value
|
[
"Increment",
"current",
"file",
"count",
"by",
"value"
] |
def increment_current_count(self, value):
"""Increment current file count by value"""
self._current_count += value
self._update_total_count()
|
[
"def",
"increment_current_count",
"(",
"self",
",",
"value",
")",
":",
"self",
".",
"_current_count",
"+=",
"value",
"self",
".",
"_update_total_count",
"(",
")"
] |
https://github.com/MeanEYE/Sunflower/blob/1024bbdde3b8e202ddad3553b321a7b6230bffc9/sunflower/gui/operation_dialog.py#L415-L418
|
||
msracver/Deformable-ConvNets
|
6aeda878a95bcb55eadffbe125804e730574de8d
|
deeplab/core/DataParallelExecutorGroup.py
|
python
|
DataParallelExecutorGroup.set_params
|
(self, arg_params, aux_params)
|
Assign, i.e. copy parameters to all the executors.
Parameters
----------
arg_params : dict
A dictionary of name to `NDArray` parameter mapping.
aux_params : dict
A dictionary of name to `NDArray` auxiliary variable mapping.
|
Assign, i.e. copy parameters to all the executors.
|
[
"Assign",
"i",
".",
"e",
".",
"copy",
"parameters",
"to",
"all",
"the",
"executors",
"."
] |
def set_params(self, arg_params, aux_params):
"""Assign, i.e. copy parameters to all the executors.
Parameters
----------
arg_params : dict
A dictionary of name to `NDArray` parameter mapping.
aux_params : dict
A dictionary of name to `NDArray` auxiliary variable mapping.
"""
for exec_ in self.execs:
exec_.copy_params_from(arg_params, aux_params)
|
[
"def",
"set_params",
"(",
"self",
",",
"arg_params",
",",
"aux_params",
")",
":",
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":",
"exec_",
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"copy_params_from",
"(",
"arg_params",
",",
"aux_params",
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https://github.com/msracver/Deformable-ConvNets/blob/6aeda878a95bcb55eadffbe125804e730574de8d/deeplab/core/DataParallelExecutorGroup.py#L313-L324
|
||
ProjectQ-Framework/ProjectQ
|
0d32c1610ba4e9aefd7f19eb52dadb4fbe5f9005
|
projectq/backends/_sim/_pysim.py
|
python
|
Simulator.emulate_time_evolution
|
(self, terms_dict, time, ids, ctrlids)
|
Apply exp(-i*time*H) to the wave function, i.e., evolves under the Hamiltonian H for a given time.
The terms in the Hamiltonian are not required to commute.
This function computes the action of the matrix exponential using ideas from Al-Mohy and Higham, 2011.
TODO: Implement better estimates for s.
Args:
terms_dict (dict): Operator dictionary (see QubitOperator.terms) defining the Hamiltonian.
time (scalar): Time to evolve for
ids (list): A list of qubit IDs to which to apply the evolution.
ctrlids (list): A list of control qubit IDs.
|
Apply exp(-i*time*H) to the wave function, i.e., evolves under the Hamiltonian H for a given time.
|
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def emulate_time_evolution(self, terms_dict, time, ids, ctrlids): # pylint: disable=too-many-locals
"""
Apply exp(-i*time*H) to the wave function, i.e., evolves under the Hamiltonian H for a given time.
The terms in the Hamiltonian are not required to commute.
This function computes the action of the matrix exponential using ideas from Al-Mohy and Higham, 2011.
TODO: Implement better estimates for s.
Args:
terms_dict (dict): Operator dictionary (see QubitOperator.terms) defining the Hamiltonian.
time (scalar): Time to evolve for
ids (list): A list of qubit IDs to which to apply the evolution.
ctrlids (list): A list of control qubit IDs.
"""
# Determine the (normalized) trace, which is nonzero only for identity terms:
trace = sum([c for (t, c) in terms_dict if len(t) == 0])
terms_dict = [(t, c) for (t, c) in terms_dict if len(t) > 0]
op_nrm = abs(time) * sum([abs(c) for (_, c) in terms_dict])
# rescale the operator by s:
scale = int(op_nrm + 1.0)
correction = _np.exp(-1j * time * trace / float(scale))
output_state = _np.copy(self._state)
mask = self._get_control_mask(ctrlids)
for _ in range(scale):
j = 0
nrm_change = 1.0
while nrm_change > 1.0e-12:
coeff = (-time * 1j) / float(scale * (j + 1))
current_state = _np.copy(self._state)
update = 0j
for term, tcoeff in terms_dict:
self._apply_term(term, ids)
self._state *= tcoeff
update += self._state
self._state = _np.copy(current_state)
update *= coeff
self._state = update
for k, _update in enumerate(update):
if (k & mask) == mask:
output_state[k] += _update
nrm_change = _np.linalg.norm(update)
j += 1
for k in range(len(update)):
if (k & mask) == mask:
output_state[k] *= correction
self._state = _np.copy(output_state)
|
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https://github.com/ProjectQ-Framework/ProjectQ/blob/0d32c1610ba4e9aefd7f19eb52dadb4fbe5f9005/projectq/backends/_sim/_pysim.py#L318-L364
|
||
LZQthePlane/Online-Realtime-Action-Recognition-based-on-OpenPose
|
33664be6ae7a26e9875f9771dc43d05a8b071dce
|
Tracking/deep_sort/track.py
|
python
|
Track.to_tlbr
|
(self)
|
return ret
|
Get current position in bounding box format `(min x, miny, max x, max y)`.
bounding box的第二种表达方式
|
Get current position in bounding box format `(min x, miny, max x, max y)`.
bounding box的第二种表达方式
|
[
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"max",
"y",
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".",
"bounding",
"box的第二种表达方式"
] |
def to_tlbr(self):
"""Get current position in bounding box format `(min x, miny, max x, max y)`.
bounding box的第二种表达方式
"""
ret = self.to_tlwh()
ret[2:] = ret[:2] + ret[2:]
return ret
|
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https://github.com/LZQthePlane/Online-Realtime-Action-Recognition-based-on-OpenPose/blob/33664be6ae7a26e9875f9771dc43d05a8b071dce/Tracking/deep_sort/track.py#L90-L96
|
|
zhl2008/awd-platform
|
0416b31abea29743387b10b3914581fbe8e7da5e
|
web_flaskbb/lib/python2.7/site-packages/flask_sqlalchemy/__init__.py
|
python
|
Pagination.iter_pages
|
(self, left_edge=2, left_current=2,
right_current=5, right_edge=2)
|
Iterates over the page numbers in the pagination. The four
parameters control the thresholds how many numbers should be produced
from the sides. Skipped page numbers are represented as `None`.
This is how you could render such a pagination in the templates:
.. sourcecode:: html+jinja
{% macro render_pagination(pagination, endpoint) %}
<div class=pagination>
{%- for page in pagination.iter_pages() %}
{% if page %}
{% if page != pagination.page %}
<a href="{{ url_for(endpoint, page=page) }}">{{ page }}</a>
{% else %}
<strong>{{ page }}</strong>
{% endif %}
{% else %}
<span class=ellipsis>…</span>
{% endif %}
{%- endfor %}
</div>
{% endmacro %}
|
Iterates over the page numbers in the pagination. The four
parameters control the thresholds how many numbers should be produced
from the sides. Skipped page numbers are represented as `None`.
This is how you could render such a pagination in the templates:
|
[
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"render",
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":"
] |
def iter_pages(self, left_edge=2, left_current=2,
right_current=5, right_edge=2):
"""Iterates over the page numbers in the pagination. The four
parameters control the thresholds how many numbers should be produced
from the sides. Skipped page numbers are represented as `None`.
This is how you could render such a pagination in the templates:
.. sourcecode:: html+jinja
{% macro render_pagination(pagination, endpoint) %}
<div class=pagination>
{%- for page in pagination.iter_pages() %}
{% if page %}
{% if page != pagination.page %}
<a href="{{ url_for(endpoint, page=page) }}">{{ page }}</a>
{% else %}
<strong>{{ page }}</strong>
{% endif %}
{% else %}
<span class=ellipsis>…</span>
{% endif %}
{%- endfor %}
</div>
{% endmacro %}
"""
last = 0
for num in xrange(1, self.pages + 1):
if num <= left_edge or \
(num > self.page - left_current - 1 and \
num < self.page + right_current) or \
num > self.pages - right_edge:
if last + 1 != num:
yield None
yield num
last = num
|
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https://github.com/zhl2008/awd-platform/blob/0416b31abea29743387b10b3914581fbe8e7da5e/web_flaskbb/lib/python2.7/site-packages/flask_sqlalchemy/__init__.py#L370-L404
|
||
OpenEndedGroup/Field
|
4f7c8edfb01bb0ccc927b78d3c500f018a4ae37c
|
Contents/lib/python/site.py
|
python
|
setquit
|
()
|
Define new built-ins 'quit' and 'exit'.
These are simply strings that display a hint on how to exit.
|
Define new built-ins 'quit' and 'exit'.
These are simply strings that display a hint on how to exit.
|
[
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"-",
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"that",
"display",
"a",
"hint",
"on",
"how",
"to",
"exit",
"."
] |
def setquit():
"""Define new built-ins 'quit' and 'exit'.
These are simply strings that display a hint on how to exit.
"""
if os.sep == ':':
eof = 'Cmd-Q'
elif os.sep == '\\':
eof = 'Ctrl-Z plus Return'
else:
eof = 'Ctrl-D (i.e. EOF)'
class Quitter(object):
def __init__(self, name):
self.name = name
def __repr__(self):
return 'Use %s() or %s to exit' % (self.name, eof)
def __call__(self, code=None):
# Shells like IDLE catch the SystemExit, but listen when their
# stdin wrapper is closed.
try:
sys.stdin.close()
except:
pass
raise SystemExit(code)
__builtin__.quit = Quitter('quit')
__builtin__.exit = Quitter('exit')
|
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https://github.com/OpenEndedGroup/Field/blob/4f7c8edfb01bb0ccc927b78d3c500f018a4ae37c/Contents/lib/python/site.py#L233-L259
|
||
jgyates/genmon
|
2cb2ed2945f55cd8c259b09ccfa9a51e23f1341e
|
genmonlib/gaugediy.py
|
python
|
GaugeDIY1.__init__
|
(self, config, log = None, console = None)
|
[] |
def __init__(self, config, log = None, console = None):
super(GaugeDIY1, self).__init__(config, log = log, console = console)
self.mv_per_step = self.config.ReadValue('mv_per_step', return_type = int, default = 125)
self.Multiplier = self.config.ReadValue('volts_to_percent_multiplier', return_type = float, default = 20.0)
self.debug = self.config.ReadValue('debug', return_type = bool, default = False)
|
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https://github.com/jgyates/genmon/blob/2cb2ed2945f55cd8c259b09ccfa9a51e23f1341e/genmonlib/gaugediy.py#L67-L73
|
||||
aws-samples/aws-kube-codesuite
|
ab4e5ce45416b83bffb947ab8d234df5437f4fca
|
src/kubernetes/client/models/v1beta1_role_binding_list.py
|
python
|
V1beta1RoleBindingList.kind
|
(self)
|
return self._kind
|
Gets the kind of this V1beta1RoleBindingList.
Kind is a string value representing the REST resource this object represents. Servers may infer this from the endpoint the client submits requests to. Cannot be updated. In CamelCase. More info: https://git.k8s.io/community/contributors/devel/api-conventions.md#types-kinds
:return: The kind of this V1beta1RoleBindingList.
:rtype: str
|
Gets the kind of this V1beta1RoleBindingList.
Kind is a string value representing the REST resource this object represents. Servers may infer this from the endpoint the client submits requests to. Cannot be updated. In CamelCase. More info: https://git.k8s.io/community/contributors/devel/api-conventions.md#types-kinds
|
[
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def kind(self):
"""
Gets the kind of this V1beta1RoleBindingList.
Kind is a string value representing the REST resource this object represents. Servers may infer this from the endpoint the client submits requests to. Cannot be updated. In CamelCase. More info: https://git.k8s.io/community/contributors/devel/api-conventions.md#types-kinds
:return: The kind of this V1beta1RoleBindingList.
:rtype: str
"""
return self._kind
|
[
"def",
"kind",
"(",
"self",
")",
":",
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] |
https://github.com/aws-samples/aws-kube-codesuite/blob/ab4e5ce45416b83bffb947ab8d234df5437f4fca/src/kubernetes/client/models/v1beta1_role_binding_list.py#L101-L109
|
|
pyparallel/pyparallel
|
11e8c6072d48c8f13641925d17b147bf36ee0ba3
|
Lib/site-packages/pip-7.1.2-py3.3.egg/pip/locations.py
|
python
|
__get_username
|
()
|
return pwd.getpwuid(os.geteuid()).pw_name
|
Returns the effective username of the current process.
|
Returns the effective username of the current process.
|
[
"Returns",
"the",
"effective",
"username",
"of",
"the",
"current",
"process",
"."
] |
def __get_username():
""" Returns the effective username of the current process. """
if WINDOWS:
return getpass.getuser()
import pwd
return pwd.getpwuid(os.geteuid()).pw_name
|
[
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"(",
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"pw_name"
] |
https://github.com/pyparallel/pyparallel/blob/11e8c6072d48c8f13641925d17b147bf36ee0ba3/Lib/site-packages/pip-7.1.2-py3.3.egg/pip/locations.py#L97-L102
|
|
brad-sp/cuckoo-modified
|
038cfbba66ef76557d255aa89f2d4205f376ca45
|
lib/cuckoo/core/startup.py
|
python
|
init_console_logging
|
()
|
Initializes logging only to console.
|
Initializes logging only to console.
|
[
"Initializes",
"logging",
"only",
"to",
"console",
"."
] |
def init_console_logging():
"""Initializes logging only to console."""
formatter = logging.Formatter("%(asctime)s [%(name)s] %(levelname)s: %(message)s")
ch = ConsoleHandler()
ch.setFormatter(formatter)
log.addHandler(ch)
log.setLevel(logging.INFO)
|
[
"def",
"init_console_logging",
"(",
")",
":",
"formatter",
"=",
"logging",
".",
"Formatter",
"(",
"\"%(asctime)s [%(name)s] %(levelname)s: %(message)s\"",
")",
"ch",
"=",
"ConsoleHandler",
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".",
"addHandler",
"(",
"ch",
")",
"log",
".",
"setLevel",
"(",
"logging",
".",
"INFO",
")"
] |
https://github.com/brad-sp/cuckoo-modified/blob/038cfbba66ef76557d255aa89f2d4205f376ca45/lib/cuckoo/core/startup.py#L151-L159
|
||
StanfordVL/taskonomy
|
9f814867b5fe4165860862211e8e99b0f200144d
|
taskbank/lib/data/load_ops.py
|
python
|
mask_if_channel_ge
|
( img, threshhold, channel_idx, broadcast_to_shape=None, broadcast_to_dim=None )
|
Returns a mask that masks an entire pixel iff the channel
specified has values ge a specified value
|
Returns a mask that masks an entire pixel iff the channel
specified has values ge a specified value
|
[
"Returns",
"a",
"mask",
"that",
"masks",
"an",
"entire",
"pixel",
"iff",
"the",
"channel",
"specified",
"has",
"values",
"ge",
"a",
"specified",
"value"
] |
def mask_if_channel_ge( img, threshhold, channel_idx, broadcast_to_shape=None, broadcast_to_dim=None ):
'''
Returns a mask that masks an entire pixel iff the channel
specified has values ge a specified value
'''
h, w, c = img.shape
mask = ( img[:, :, channel_idx] < threshhold ) # keep if lt
if len( mask.shape ) == 2:
mask = mask[:, :, np.newaxis].astype( np.float32 )
if broadcast_to_shape is not None:
return np.broadcast_to( mask, broadcast_to_shape )
elif broadcast_to_dim is not None:
return np.broadcast_to( mask, [h,w,broadcast_to_dim])
else:
return np.broadcast_to( mask, img.shape )
|
[
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] |
https://github.com/StanfordVL/taskonomy/blob/9f814867b5fe4165860862211e8e99b0f200144d/taskbank/lib/data/load_ops.py#L1531-L1545
|
||
zhl2008/awd-platform
|
0416b31abea29743387b10b3914581fbe8e7da5e
|
web_flaskbb/lib/python2.7/site-packages/werkzeug/datastructures.py
|
python
|
ImmutableHeadersMixin.setdefault
|
(self, key, default)
|
[] |
def setdefault(self, key, default):
is_immutable(self)
|
[
"def",
"setdefault",
"(",
"self",
",",
"key",
",",
"default",
")",
":",
"is_immutable",
"(",
"self",
")"
] |
https://github.com/zhl2008/awd-platform/blob/0416b31abea29743387b10b3914581fbe8e7da5e/web_flaskbb/lib/python2.7/site-packages/werkzeug/datastructures.py#L1322-L1323
|
||||
fortharris/Pcode
|
147962d160a834c219e12cb456abc130826468e4
|
rope/base/evaluate.py
|
python
|
StatementEvaluator._Compare
|
(self, node)
|
[] |
def _Compare(self, node):
self.result = self._get_builtin_name('bool')
|
[
"def",
"_Compare",
"(",
"self",
",",
"node",
")",
":",
"self",
".",
"result",
"=",
"self",
".",
"_get_builtin_name",
"(",
"'bool'",
")"
] |
https://github.com/fortharris/Pcode/blob/147962d160a834c219e12cb456abc130826468e4/rope/base/evaluate.py#L214-L215
|
||||
sensepost/objection
|
658675f0e7716bd0899c9f6e9c45d25f38a699d8
|
objection/commands/sqlite.py
|
python
|
_should_sync_once_done
|
(args: list)
|
return '--sync' in args
|
Checks if --sync flag was provided.
:param args:
:return:
|
Checks if --sync flag was provided.
|
[
"Checks",
"if",
"--",
"sync",
"flag",
"was",
"provided",
"."
] |
def _should_sync_once_done(args: list) -> bool:
"""
Checks if --sync flag was provided.
:param args:
:return:
"""
return '--sync' in args
|
[
"def",
"_should_sync_once_done",
"(",
"args",
":",
"list",
")",
"->",
"bool",
":",
"return",
"'--sync'",
"in",
"args"
] |
https://github.com/sensepost/objection/blob/658675f0e7716bd0899c9f6e9c45d25f38a699d8/objection/commands/sqlite.py#L43-L51
|
|
wwqgtxx/wwqLyParse
|
33136508e52821babd9294fdecffbdf02d73a6fc
|
wwqLyParse/lib/aiohttp_lib_py352/aiohttp/web.py
|
python
|
run_app
|
(app, *, host=None, port=None, path=None, sock=None,
shutdown_timeout=60.0, ssl_context=None,
print=print, backlog=128, access_log_format=None,
access_log=access_logger, handle_signals=True, loop=None)
|
Run an app locally
|
Run an app locally
|
[
"Run",
"an",
"app",
"locally"
] |
def run_app(app, *, host=None, port=None, path=None, sock=None,
shutdown_timeout=60.0, ssl_context=None,
print=print, backlog=128, access_log_format=None,
access_log=access_logger, handle_signals=True, loop=None):
"""Run an app locally"""
user_supplied_loop = loop is not None
if loop is None:
loop = asyncio.get_event_loop()
app._set_loop(loop)
loop.run_until_complete(app.startup())
try:
make_handler_kwargs = dict()
if access_log_format is not None:
make_handler_kwargs['access_log_format'] = access_log_format
handler = app.make_handler(loop=loop, access_log=access_log,
**make_handler_kwargs)
server_creations, uris = _make_server_creators(
handler,
loop=loop, ssl_context=ssl_context,
host=host, port=port, path=path, sock=sock,
backlog=backlog)
servers = loop.run_until_complete(
asyncio.gather(*server_creations, loop=loop)
)
if handle_signals:
try:
loop.add_signal_handler(signal.SIGINT, raise_graceful_exit)
loop.add_signal_handler(signal.SIGTERM, raise_graceful_exit)
except NotImplementedError: # pragma: no cover
# add_signal_handler is not implemented on Windows
pass
try:
if print:
print("======== Running on {} ========\n"
"(Press CTRL+C to quit)".format(', '.join(uris)))
loop.run_forever()
except (GracefulExit, KeyboardInterrupt): # pragma: no cover
pass
finally:
server_closures = []
for srv in servers:
srv.close()
server_closures.append(srv.wait_closed())
loop.run_until_complete(
asyncio.gather(*server_closures, loop=loop))
loop.run_until_complete(app.shutdown())
loop.run_until_complete(handler.shutdown(shutdown_timeout))
finally:
loop.run_until_complete(app.cleanup())
if not user_supplied_loop:
if hasattr(loop, 'shutdown_asyncgens'):
loop.run_until_complete(loop.shutdown_asyncgens())
loop.close()
|
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] |
https://github.com/wwqgtxx/wwqLyParse/blob/33136508e52821babd9294fdecffbdf02d73a6fc/wwqLyParse/lib/aiohttp_lib_py352/aiohttp/web.py#L432-L489
|
||
wucng/TensorExpand
|
4ea58f64f5c5082b278229b799c9f679536510b7
|
TensorExpand/Object detection/Mask RCNN/Mask_RCNN Exercise/train.py
|
python
|
ShapesDataset.load_shapes
|
(self, count, height, width)
|
for i in range(count):
comb_image, mask, class_ids = self.random_image(height, width)
self.add_image("shapes", image_id=i, path=None,
width=width, height=height,
image=comb_image, mask=mask, class_ids=class_ids)
|
for i in range(count):
comb_image, mask, class_ids = self.random_image(height, width)
self.add_image("shapes", image_id=i, path=None,
width=width, height=height,
image=comb_image, mask=mask, class_ids=class_ids)
|
[
"for",
"i",
"in",
"range",
"(",
"count",
")",
":",
"comb_image",
"mask",
"class_ids",
"=",
"self",
".",
"random_image",
"(",
"height",
"width",
")",
"self",
".",
"add_image",
"(",
"shapes",
"image_id",
"=",
"i",
"path",
"=",
"None",
"width",
"=",
"width",
"height",
"=",
"height",
"image",
"=",
"comb_image",
"mask",
"=",
"mask",
"class_ids",
"=",
"class_ids",
")"
] |
def load_shapes(self, count, height, width):
data=self.load_pkl()
class_dict=data[0][0] # 所有类别字典 从1开始
# self.add_class("shapes", 0, 'BG') # 标签0默认为背景 utils中已经添加了 这里不用再添加
# self.add_class("shapes", 1, "square")
# self.add_class("shapes", 2, "circle")
# self.add_class("shapes", 3, "triangle")
# 必须从1、2、3、……开始添加，否则会出错 ，下面这种情况会导致标签对不上
# [self.add_class('shapes',class_dict[i],i) for i in list(class_dict.keys())] # 无序添加会导致标签对应不上
# class id反算出class name
class_name_dict = dict(zip(class_dict.values(), class_dict.keys()))
[self.add_class('shapes',i,class_name_dict[i]) for i in range(1,21)] # 共20类
'''
for i in range(count):
comb_image, mask, class_ids = self.random_image(height, width)
self.add_image("shapes", image_id=i, path=None,
width=width, height=height,
image=comb_image, mask=mask, class_ids=class_ids)
'''
for i in range(1,len(data)):
comb_image=data[i][0]
mask=data[i][1]
class_ids=data[i][2]
self.add_image("shapes", image_id=i-1, path=None,
width=height, height=width,
image=comb_image, mask=mask, class_ids=class_ids)
|
[
"def",
"load_shapes",
"(",
"self",
",",
"count",
",",
"height",
",",
"width",
")",
":",
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")",
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"[",
"0",
"]",
"[",
"0",
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"# 所有类别字典 从1开始",
"# self.add_class(\"shapes\", 0, 'BG') # 标签0默认为背景 utils中已经添加了 这里不用再添加",
"# self.add_class(\"shapes\", 1, \"square\")",
"# self.add_class(\"shapes\", 2, \"circle\")",
"# self.add_class(\"shapes\", 3, \"triangle\")",
"# 必须从1、2、3、……开始添加，否则会出错 ，下面这种情况会导致标签对不上",
"# [self.add_class('shapes',class_dict[i],i) for i in list(class_dict.keys())] # 无序添加会导致标签对应不上",
"# class id反算出class name",
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",",
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",",
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"class_ids",
")"
] |
https://github.com/wucng/TensorExpand/blob/4ea58f64f5c5082b278229b799c9f679536510b7/TensorExpand/Object detection/Mask RCNN/Mask_RCNN Exercise/train.py#L124-L155
|
||
home-assistant/core
|
265ebd17a3f17ed8dc1e9bdede03ac8e323f1ab1
|
homeassistant/components/somfy/cover.py
|
python
|
SomfyCover.stop_cover_tilt
|
(self, **kwargs)
|
Stop the cover.
|
Stop the cover.
|
[
"Stop",
"the",
"cover",
"."
] |
def stop_cover_tilt(self, **kwargs):
"""Stop the cover."""
self._cover.stop()
|
[
"def",
"stop_cover_tilt",
"(",
"self",
",",
"*",
"*",
"kwargs",
")",
":",
"self",
".",
"_cover",
".",
"stop",
"(",
")"
] |
https://github.com/home-assistant/core/blob/265ebd17a3f17ed8dc1e9bdede03ac8e323f1ab1/homeassistant/components/somfy/cover.py#L189-L191
|
||
tanghaibao/jcvi
|
5e720870c0928996f8b77a38208106ff0447ccb6
|
jcvi/formats/fasta.py
|
python
|
sort
|
(args)
|
return sortedfastafile
|
%prog sort fastafile
Sort a list of sequences and output with sorted IDs, etc.
|
%prog sort fastafile
|
[
"%prog",
"sort",
"fastafile"
] |
def sort(args):
"""
%prog sort fastafile
Sort a list of sequences and output with sorted IDs, etc.
"""
p = OptionParser(sort.__doc__)
p.add_option(
"--sizes", default=False, action="store_true", help="Sort by decreasing size"
)
opts, args = p.parse_args(args)
if len(args) != 1:
sys.exit(p.print_help())
(fastafile,) = args
sortedfastafile = fastafile.rsplit(".", 1)[0] + ".sorted.fasta"
f = Fasta(fastafile, index=False)
fw = must_open(sortedfastafile, "w")
if opts.sizes:
# Sort by decreasing size
sortlist = sorted(f.itersizes(), key=lambda x: (-x[1], x[0]))
logging.debug(
"Sort by size: max: {0}, min: {1}".format(sortlist[0], sortlist[-1])
)
sortlist = [x for x, s in sortlist]
else:
sortlist = sorted(f.iterkeys())
for key in sortlist:
rec = f[key]
SeqIO.write([rec], fw, "fasta")
logging.debug("Sorted file written to `{0}`.".format(sortedfastafile))
fw.close()
return sortedfastafile
|
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https://github.com/tanghaibao/jcvi/blob/5e720870c0928996f8b77a38208106ff0447ccb6/jcvi/formats/fasta.py#L1092-L1130
|
|
sony/nnabla-examples
|
068be490aacf73740502a1c3b10f8b2d15a52d32
|
object-detection/centernet/src/lib/utils/voc_eval_lib/voc_datasets/pascal_voc.py
|
python
|
pascal_voc._get_default_path
|
(self, path=None)
|
Return the set path to PASCAL VOC.
|
Return the set path to PASCAL VOC.
|
[
"Return",
"the",
"set",
"path",
"to",
"PASCAL",
"VOC",
"."
] |
def _get_default_path(self, path=None):
"""
Return the set path to PASCAL VOC.
"""
if path is None:
# Return the default path where PASCAL VOC is expected to be installed.
return os.path.join(cfg.DATA_DIR, 'voc', 'VOCdevkit')
else:
return os.path.join(path, 'voc', 'VOCdevkit')
|
[
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https://github.com/sony/nnabla-examples/blob/068be490aacf73740502a1c3b10f8b2d15a52d32/object-detection/centernet/src/lib/utils/voc_eval_lib/voc_datasets/pascal_voc.py#L104-L112
|
||
requests/requests-oauthlib
|
05a25a96522dc64c25224a4862f2342a6978e80d
|
requests_oauthlib/oauth1_session.py
|
python
|
OAuth1Session.authorization_url
|
(self, url, request_token=None, **kwargs)
|
return add_params_to_uri(url, kwargs.items())
|
Create an authorization URL by appending request_token and optional
kwargs to url.
This is the second step in the OAuth 1 workflow. The user should be
redirected to this authorization URL, grant access to you, and then
be redirected back to you. The redirection back can either be specified
during client registration or by supplying a callback URI per request.
:param url: The authorization endpoint URL.
:param request_token: The previously obtained request token.
:param kwargs: Optional parameters to append to the URL.
:returns: The authorization URL with new parameters embedded.
An example using a registered default callback URI.
>>> request_token_url = 'https://api.twitter.com/oauth/request_token'
>>> authorization_url = 'https://api.twitter.com/oauth/authorize'
>>> oauth_session = OAuth1Session('client-key', client_secret='secret')
>>> oauth_session.fetch_request_token(request_token_url)
{
'oauth_token': 'sdf0o9823sjdfsdf',
'oauth_token_secret': '2kjshdfp92i34asdasd',
}
>>> oauth_session.authorization_url(authorization_url)
'https://api.twitter.com/oauth/authorize?oauth_token=sdf0o9823sjdfsdf'
>>> oauth_session.authorization_url(authorization_url, foo='bar')
'https://api.twitter.com/oauth/authorize?oauth_token=sdf0o9823sjdfsdf&foo=bar'
An example using an explicit callback URI.
>>> request_token_url = 'https://api.twitter.com/oauth/request_token'
>>> authorization_url = 'https://api.twitter.com/oauth/authorize'
>>> oauth_session = OAuth1Session('client-key', client_secret='secret', callback_uri='https://127.0.0.1/callback')
>>> oauth_session.fetch_request_token(request_token_url)
{
'oauth_token': 'sdf0o9823sjdfsdf',
'oauth_token_secret': '2kjshdfp92i34asdasd',
}
>>> oauth_session.authorization_url(authorization_url)
'https://api.twitter.com/oauth/authorize?oauth_token=sdf0o9823sjdfsdf&oauth_callback=https%3A%2F%2F127.0.0.1%2Fcallback'
|
Create an authorization URL by appending request_token and optional
kwargs to url.
|
[
"Create",
"an",
"authorization",
"URL",
"by",
"appending",
"request_token",
"and",
"optional",
"kwargs",
"to",
"url",
"."
] |
def authorization_url(self, url, request_token=None, **kwargs):
"""Create an authorization URL by appending request_token and optional
kwargs to url.
This is the second step in the OAuth 1 workflow. The user should be
redirected to this authorization URL, grant access to you, and then
be redirected back to you. The redirection back can either be specified
during client registration or by supplying a callback URI per request.
:param url: The authorization endpoint URL.
:param request_token: The previously obtained request token.
:param kwargs: Optional parameters to append to the URL.
:returns: The authorization URL with new parameters embedded.
An example using a registered default callback URI.
>>> request_token_url = 'https://api.twitter.com/oauth/request_token'
>>> authorization_url = 'https://api.twitter.com/oauth/authorize'
>>> oauth_session = OAuth1Session('client-key', client_secret='secret')
>>> oauth_session.fetch_request_token(request_token_url)
{
'oauth_token': 'sdf0o9823sjdfsdf',
'oauth_token_secret': '2kjshdfp92i34asdasd',
}
>>> oauth_session.authorization_url(authorization_url)
'https://api.twitter.com/oauth/authorize?oauth_token=sdf0o9823sjdfsdf'
>>> oauth_session.authorization_url(authorization_url, foo='bar')
'https://api.twitter.com/oauth/authorize?oauth_token=sdf0o9823sjdfsdf&foo=bar'
An example using an explicit callback URI.
>>> request_token_url = 'https://api.twitter.com/oauth/request_token'
>>> authorization_url = 'https://api.twitter.com/oauth/authorize'
>>> oauth_session = OAuth1Session('client-key', client_secret='secret', callback_uri='https://127.0.0.1/callback')
>>> oauth_session.fetch_request_token(request_token_url)
{
'oauth_token': 'sdf0o9823sjdfsdf',
'oauth_token_secret': '2kjshdfp92i34asdasd',
}
>>> oauth_session.authorization_url(authorization_url)
'https://api.twitter.com/oauth/authorize?oauth_token=sdf0o9823sjdfsdf&oauth_callback=https%3A%2F%2F127.0.0.1%2Fcallback'
"""
kwargs["oauth_token"] = request_token or self._client.client.resource_owner_key
log.debug("Adding parameters %s to url %s", kwargs, url)
return add_params_to_uri(url, kwargs.items())
|
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https://github.com/requests/requests-oauthlib/blob/05a25a96522dc64c25224a4862f2342a6978e80d/requests_oauthlib/oauth1_session.py#L214-L258
|
|
bayespy/bayespy
|
0e6e6130c888a4295cc9421d61d4ad27b2960ebb
|
bayespy/utils/linalg.py
|
python
|
inv
|
(A, ndim=1)
|
General array inversion.
Supports broadcasting and inversion of multidimensional arrays. For
instance, an array with shape (4,3,2,3,2) could mean that there are four
(3*2) x (3*2) matrices to be inverted. This can be done by inv(A, ndim=2).
For inverting scalars, ndim=0. For inverting matrices, ndim=1.
|
General array inversion.
|
[
"General",
"array",
"inversion",
"."
] |
def inv(A, ndim=1):
"""
General array inversion.
Supports broadcasting and inversion of multidimensional arrays. For
instance, an array with shape (4,3,2,3,2) could mean that there are four
(3*2) x (3*2) matrices to be inverted. This can be done by inv(A, ndim=2).
For inverting scalars, ndim=0. For inverting matrices, ndim=1.
"""
A = np.asanyarray(A)
if ndim == 0:
return 1 / A
elif ndim == 1:
return np.linalg.inv(A)
else:
raise NotImplementedError()
|
[
"def",
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https://github.com/bayespy/bayespy/blob/0e6e6130c888a4295cc9421d61d4ad27b2960ebb/bayespy/utils/linalg.py#L389-L404
|
||
projecthamster/hamster
|
19d160090de30e756bdc3122ff935bdaa86e2843
|
waflib/Task.py
|
python
|
Task.runnable_status
|
(self)
|
return (self.always_run and RUN_ME) or SKIP_ME
|
Returns the Task status
:return: a task state in :py:const:`waflib.Task.RUN_ME`,
:py:const:`waflib.Task.SKIP_ME`, :py:const:`waflib.Task.CANCEL_ME` or :py:const:`waflib.Task.ASK_LATER`.
:rtype: int
|
Returns the Task status
|
[
"Returns",
"the",
"Task",
"status"
] |
def runnable_status(self):
"""
Returns the Task status
:return: a task state in :py:const:`waflib.Task.RUN_ME`,
:py:const:`waflib.Task.SKIP_ME`, :py:const:`waflib.Task.CANCEL_ME` or :py:const:`waflib.Task.ASK_LATER`.
:rtype: int
"""
bld = self.generator.bld
if bld.is_install < 0:
return SKIP_ME
for t in self.run_after:
if not t.hasrun:
return ASK_LATER
elif t.hasrun < SKIPPED:
# a dependency has an error
return CANCEL_ME
# first compute the signature
try:
new_sig = self.signature()
except Errors.TaskNotReady:
return ASK_LATER
# compare the signature to a signature computed previously
key = self.uid()
try:
prev_sig = bld.task_sigs[key]
except KeyError:
Logs.debug('task: task %r must run: it was never run before or the task code changed', self)
return RUN_ME
if new_sig != prev_sig:
Logs.debug('task: task %r must run: the task signature changed', self)
return RUN_ME
# compare the signatures of the outputs
for node in self.outputs:
sig = bld.node_sigs.get(node)
if not sig:
Logs.debug('task: task %r must run: an output node has no signature', self)
return RUN_ME
if sig != key:
Logs.debug('task: task %r must run: an output node was produced by another task', self)
return RUN_ME
if not node.exists():
Logs.debug('task: task %r must run: an output node does not exist', self)
return RUN_ME
return (self.always_run and RUN_ME) or SKIP_ME
|
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"(",
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"RUN_ME",
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] |
https://github.com/projecthamster/hamster/blob/19d160090de30e756bdc3122ff935bdaa86e2843/waflib/Task.py#L658-L708
|
|
TarrySingh/Artificial-Intelligence-Deep-Learning-Machine-Learning-Tutorials
|
5bb97d7e3ffd913abddb4cfa7d78a1b4c868890e
|
scipy/thinkstats2.py
|
python
|
PmfProbGreater
|
(pmf1, pmf2)
|
return total
|
Probability that a value from pmf1 is less than a value from pmf2.
Args:
pmf1: Pmf object
pmf2: Pmf object
Returns:
float probability
|
Probability that a value from pmf1 is less than a value from pmf2.
|
[
"Probability",
"that",
"a",
"value",
"from",
"pmf1",
"is",
"less",
"than",
"a",
"value",
"from",
"pmf2",
"."
] |
def PmfProbGreater(pmf1, pmf2):
"""Probability that a value from pmf1 is less than a value from pmf2.
Args:
pmf1: Pmf object
pmf2: Pmf object
Returns:
float probability
"""
total = 0.0
for v1, p1 in pmf1.Items():
for v2, p2 in pmf2.Items():
if v1 > v2:
total += p1 * p2
return total
|
[
"def",
"PmfProbGreater",
"(",
"pmf1",
",",
"pmf2",
")",
":",
"total",
"=",
"0.0",
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">",
"v2",
":",
"total",
"+=",
"p1",
"*",
"p2",
"return",
"total"
] |
https://github.com/TarrySingh/Artificial-Intelligence-Deep-Learning-Machine-Learning-Tutorials/blob/5bb97d7e3ffd913abddb4cfa7d78a1b4c868890e/scipy/thinkstats2.py#L1665-L1680
|
|
IronLanguages/ironpython3
|
7a7bb2a872eeab0d1009fc8a6e24dca43f65b693
|
Src/StdLib/Lib/collections/__init__.py
|
python
|
Counter.__delitem__
|
(self, elem)
|
Like dict.__delitem__() but does not raise KeyError for missing values.
|
Like dict.__delitem__() but does not raise KeyError for missing values.
|
[
"Like",
"dict",
".",
"__delitem__",
"()",
"but",
"does",
"not",
"raise",
"KeyError",
"for",
"missing",
"values",
"."
] |
def __delitem__(self, elem):
'Like dict.__delitem__() but does not raise KeyError for missing values.'
if elem in self:
super().__delitem__(elem)
|
[
"def",
"__delitem__",
"(",
"self",
",",
"elem",
")",
":",
"if",
"elem",
"in",
"self",
":",
"super",
"(",
")",
".",
"__delitem__",
"(",
"elem",
")"
] |
https://github.com/IronLanguages/ironpython3/blob/7a7bb2a872eeab0d1009fc8a6e24dca43f65b693/Src/StdLib/Lib/collections/__init__.py#L598-L601
|
||
python-streamz/streamz
|
8744c83a0fad1fbd9ee9318d1a79ee538415a4e4
|
streamz/collection.py
|
python
|
OperatorMixin.__mod__
|
(self, other)
|
return self.map_partitions(operator.mod, self, other)
|
[] |
def __mod__(self, other):
return self.map_partitions(operator.mod, self, other)
|
[
"def",
"__mod__",
"(",
"self",
",",
"other",
")",
":",
"return",
"self",
".",
"map_partitions",
"(",
"operator",
".",
"mod",
",",
"self",
",",
"other",
")"
] |
https://github.com/python-streamz/streamz/blob/8744c83a0fad1fbd9ee9318d1a79ee538415a4e4/streamz/collection.py#L100-L101
|
|||
python-telegram-bot/python-telegram-bot
|
ade1529986f5b6d394a65372d6a27045a70725b2
|
telegram/bot.py
|
python
|
Bot.edit_chat_invite_link
|
(
self,
chat_id: Union[str, int],
invite_link: str,
expire_date: Union[int, datetime] = None,
member_limit: int = None,
timeout: ODVInput[float] = DEFAULT_NONE,
api_kwargs: JSONDict = None,
name: str = None,
creates_join_request: bool = None,
)
|
return ChatInviteLink.de_json(result, self)
|
Use this method to edit a non-primary invite link created by the bot. The bot must be an
administrator in the chat for this to work and must have the appropriate admin rights.
Note:
Though not stated explicitly in the official docs, Telegram changes not only the
optional parameters that are explicitly passed, but also replaces all other optional
parameters to the default values. However, since not documented, this behaviour may
change unbeknown to PTB.
.. versionadded:: 13.4
Args:
chat_id (:obj:`int` | :obj:`str`): Unique identifier for the target chat or username
of the target channel (in the format ``@channelusername``).
invite_link (:obj:`str`): The invite link to edit.
expire_date (:obj:`int` | :obj:`datetime.datetime`, optional): Date when the link will
expire.
For timezone naive :obj:`datetime.datetime` objects, the default timezone of the
bot will be used.
member_limit (:obj:`int`, optional): Maximum number of users that can be members of
the chat simultaneously after joining the chat via this invite link; 1-99999.
timeout (:obj:`int` | :obj:`float`, optional): If this value is specified, use it as
the read timeout from the server (instead of the one specified during creation of
the connection pool).
api_kwargs (:obj:`dict`, optional): Arbitrary keyword arguments to be passed to the
Telegram API.
name (:obj:`str`, optional): Invite link name; 0-32 characters.
.. versionadded:: 13.8
creates_join_request (:obj:`bool`, optional): :obj:`True`, if users joining the chat
via the link need to be approved by chat administrators.
If :obj:`True`, ``member_limit`` can't be specified.
.. versionadded:: 13.8
Returns:
:class:`telegram.ChatInviteLink`
Raises:
:class:`telegram.error.TelegramError`
|
Use this method to edit a non-primary invite link created by the bot. The bot must be an
administrator in the chat for this to work and must have the appropriate admin rights.
|
[
"Use",
"this",
"method",
"to",
"edit",
"a",
"non",
"-",
"primary",
"invite",
"link",
"created",
"by",
"the",
"bot",
".",
"The",
"bot",
"must",
"be",
"an",
"administrator",
"in",
"the",
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"for",
"this",
"to",
"work",
"and",
"must",
"have",
"the",
"appropriate",
"admin",
"rights",
"."
] |
def edit_chat_invite_link(
self,
chat_id: Union[str, int],
invite_link: str,
expire_date: Union[int, datetime] = None,
member_limit: int = None,
timeout: ODVInput[float] = DEFAULT_NONE,
api_kwargs: JSONDict = None,
name: str = None,
creates_join_request: bool = None,
) -> ChatInviteLink:
"""
Use this method to edit a non-primary invite link created by the bot. The bot must be an
administrator in the chat for this to work and must have the appropriate admin rights.
Note:
Though not stated explicitly in the official docs, Telegram changes not only the
optional parameters that are explicitly passed, but also replaces all other optional
parameters to the default values. However, since not documented, this behaviour may
change unbeknown to PTB.
.. versionadded:: 13.4
Args:
chat_id (:obj:`int` | :obj:`str`): Unique identifier for the target chat or username
of the target channel (in the format ``@channelusername``).
invite_link (:obj:`str`): The invite link to edit.
expire_date (:obj:`int` | :obj:`datetime.datetime`, optional): Date when the link will
expire.
For timezone naive :obj:`datetime.datetime` objects, the default timezone of the
bot will be used.
member_limit (:obj:`int`, optional): Maximum number of users that can be members of
the chat simultaneously after joining the chat via this invite link; 1-99999.
timeout (:obj:`int` | :obj:`float`, optional): If this value is specified, use it as
the read timeout from the server (instead of the one specified during creation of
the connection pool).
api_kwargs (:obj:`dict`, optional): Arbitrary keyword arguments to be passed to the
Telegram API.
name (:obj:`str`, optional): Invite link name; 0-32 characters.
.. versionadded:: 13.8
creates_join_request (:obj:`bool`, optional): :obj:`True`, if users joining the chat
via the link need to be approved by chat administrators.
If :obj:`True`, ``member_limit`` can't be specified.
.. versionadded:: 13.8
Returns:
:class:`telegram.ChatInviteLink`
Raises:
:class:`telegram.error.TelegramError`
"""
if creates_join_request and member_limit:
raise ValueError(
"If `creates_join_request` is `True`, `member_limit` can't be specified."
)
data: JSONDict = {'chat_id': chat_id, 'invite_link': invite_link}
if expire_date is not None:
if isinstance(expire_date, datetime):
expire_date = to_timestamp(
expire_date, tzinfo=self.defaults.tzinfo if self.defaults else None
)
data['expire_date'] = expire_date
if member_limit is not None:
data['member_limit'] = member_limit
if name is not None:
data['name'] = name
if creates_join_request is not None:
data['creates_join_request'] = creates_join_request
result = self._post('editChatInviteLink', data, timeout=timeout, api_kwargs=api_kwargs)
return ChatInviteLink.de_json(result, self)
|
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")",
"return",
"ChatInviteLink",
".",
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"(",
"result",
",",
"self",
")"
] |
https://github.com/python-telegram-bot/python-telegram-bot/blob/ade1529986f5b6d394a65372d6a27045a70725b2/telegram/bot.py#L4258-L4337
|
|
tendenci/tendenci
|
0f2c348cc0e7d41bc56f50b00ce05544b083bf1d
|
tendenci/apps/boxes/utils.py
|
python
|
render_content
|
(content, arg=None, limit=None, image_preview=True)
|
return content
|
checks for template tags within the content and rendered them
currently it is only rendering streams
|
checks for template tags within the content and rendered them
currently it is only rendering streams
|
[
"checks",
"for",
"template",
"tags",
"within",
"the",
"content",
"and",
"rendered",
"them",
"currently",
"it",
"is",
"only",
"rendering",
"streams"
] |
def render_content(content, arg=None, limit=None, image_preview=True):
"""
checks for template tags within the content and rendered them
currently it is only rendering streams
"""
match = detect_template_tags(content)
if match:
p = re.compile(r'{%([\w\s\=]+)%}')
tags = list(set(re.findall(p, content)))
TEMPLATE_TAGS = ['{% load box_tags %}']
if tags:
for tag in tags:
tag = "{%"+tag+"%}"
t = engines['django'].from_string(''.join(TEMPLATE_TAGS) + tag)
rendered_tag = t.render(context={'user': None})
content = content.replace(tag, rendered_tag)
return content
|
[
"def",
"render_content",
"(",
"content",
",",
"arg",
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"None",
",",
"limit",
"=",
"None",
",",
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":",
"match",
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"findall",
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"}",
")",
"content",
"=",
"content",
".",
"replace",
"(",
"tag",
",",
"rendered_tag",
")",
"return",
"content"
] |
https://github.com/tendenci/tendenci/blob/0f2c348cc0e7d41bc56f50b00ce05544b083bf1d/tendenci/apps/boxes/utils.py#L15-L32
|
|
tendenci/tendenci
|
0f2c348cc0e7d41bc56f50b00ce05544b083bf1d
|
tendenci/apps/help_files/views.py
|
python
|
export
|
(request, template_name="help_files/export.html")
|
return render_to_resp(request=request, template_name=template_name, context={
})
|
Export Help Files
|
Export Help Files
|
[
"Export",
"Help",
"Files"
] |
def export(request, template_name="help_files/export.html"):
"""Export Help Files"""
if not request.user.is_superuser:
raise Http403
if request.method == 'POST':
# initilize initial values
fields = [
'slug',
'topics',
'question',
'answer',
'level',
'is_faq',
'is_featured',
'is_video',
'syndicate',
'view_totals',
]
export_id = run_export_task('help_files', 'helpfile', fields)
EventLog.objects.log()
return redirect('export.status', export_id)
return render_to_resp(request=request, template_name=template_name, context={
})
|
[
"def",
"export",
"(",
"request",
",",
"template_name",
"=",
"\"help_files/export.html\"",
")",
":",
"if",
"not",
"request",
".",
"user",
".",
"is_superuser",
":",
"raise",
"Http403",
"if",
"request",
".",
"method",
"==",
"'POST'",
":",
"# initilize initial values",
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"=",
"[",
"'slug'",
",",
"'topics'",
",",
"'question'",
",",
"'answer'",
",",
"'level'",
",",
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",",
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",",
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",",
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",",
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",",
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"'help_files'",
",",
"'helpfile'",
",",
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",",
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"=",
"request",
",",
"template_name",
"=",
"template_name",
",",
"context",
"=",
"{",
"}",
")"
] |
https://github.com/tendenci/tendenci/blob/0f2c348cc0e7d41bc56f50b00ce05544b083bf1d/tendenci/apps/help_files/views.py#L229-L254
|
|
CenterForOpenScience/osf.io
|
cc02691be017e61e2cd64f19b848b2f4c18dcc84
|
website/conferences/utils.py
|
python
|
provision_node
|
(conference, message, node, user)
|
:param Conference conference:
:param ConferenceMessage message:
:param Node node:
:param User user:
|
:param Conference conference:
:param ConferenceMessage message:
:param Node node:
:param User user:
|
[
":",
"param",
"Conference",
"conference",
":",
":",
"param",
"ConferenceMessage",
"message",
":",
":",
"param",
"Node",
"node",
":",
":",
"param",
"User",
"user",
":"
] |
def provision_node(conference, message, node, user):
"""
:param Conference conference:
:param ConferenceMessage message:
:param Node node:
:param User user:
"""
auth = Auth(user=user)
try:
wiki = WikiPage.objects.create_for_node(node, 'home', message.text, auth)
except NodeStateError:
wiki = WikiPage.objects.get_for_node(node, 'home')
wiki.update(user, message.text)
if conference.admins.exists():
node.add_contributors(prepare_contributors(conference.admins.all()), log=False)
if not message.is_spam and conference.public_projects:
node.set_privacy('public', meeting_creation=True, auth=auth)
conference.submissions.add(node)
node.add_tag(message.conference_category, auth=auth)
for systag in ['emailed', message.conference_name, message.conference_category]:
node.add_system_tag(systag, save=False)
if message.is_spam:
node.add_system_tag('spam', save=False)
node.save()
|
[
"def",
"provision_node",
"(",
"conference",
",",
"message",
",",
"node",
",",
"user",
")",
":",
"auth",
"=",
"Auth",
"(",
"user",
"=",
"user",
")",
"try",
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"WikiPage",
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",",
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"[",
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",",
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",",
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",",
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"False",
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"(",
"'spam'",
",",
"save",
"=",
"False",
")",
"node",
".",
"save",
"(",
")"
] |
https://github.com/CenterForOpenScience/osf.io/blob/cc02691be017e61e2cd64f19b848b2f4c18dcc84/website/conferences/utils.py#L25-L52
|
||
Fantomas42/django-blog-zinnia
|
881101a9d1d455b2fc581d6f4ae0947cdd8126c6
|
zinnia/calendar.py
|
python
|
Calendar.formatmonthname
|
(self, theyear, themonth, withyear=True)
|
return '<caption>%s</caption>' % monthname
|
Return a month name translated as a table row.
|
Return a month name translated as a table row.
|
[
"Return",
"a",
"month",
"name",
"translated",
"as",
"a",
"table",
"row",
"."
] |
def formatmonthname(self, theyear, themonth, withyear=True):
"""Return a month name translated as a table row."""
monthname = '%s %s' % (MONTHS[themonth].title(), theyear)
return '<caption>%s</caption>' % monthname
|
[
"def",
"formatmonthname",
"(",
"self",
",",
"theyear",
",",
"themonth",
",",
"withyear",
"=",
"True",
")",
":",
"monthname",
"=",
"'%s %s'",
"%",
"(",
"MONTHS",
"[",
"themonth",
"]",
".",
"title",
"(",
")",
",",
"theyear",
")",
"return",
"'<caption>%s</caption>'",
"%",
"monthname"
] |
https://github.com/Fantomas42/django-blog-zinnia/blob/881101a9d1d455b2fc581d6f4ae0947cdd8126c6/zinnia/calendar.py#L90-L93
|
|
KalleHallden/AutoTimer
|
2d954216700c4930baa154e28dbddc34609af7ce
|
env/lib/python2.7/site-packages/pkg_resources/_vendor/packaging/specifiers.py
|
python
|
LegacySpecifier._coerce_version
|
(self, version)
|
return version
|
[] |
def _coerce_version(self, version):
if not isinstance(version, LegacyVersion):
version = LegacyVersion(str(version))
return version
|
[
"def",
"_coerce_version",
"(",
"self",
",",
"version",
")",
":",
"if",
"not",
"isinstance",
"(",
"version",
",",
"LegacyVersion",
")",
":",
"version",
"=",
"LegacyVersion",
"(",
"str",
"(",
"version",
")",
")",
"return",
"version"
] |
https://github.com/KalleHallden/AutoTimer/blob/2d954216700c4930baa154e28dbddc34609af7ce/env/lib/python2.7/site-packages/pkg_resources/_vendor/packaging/specifiers.py#L242-L245
|
|||
mopidy/mopidy
|
796ebe9b4e1fe7efdb24199cda810492dcb903a1
|
mopidy/audio/utils.py
|
python
|
calculate_duration
|
(num_samples, sample_rate)
|
return Gst.util_uint64_scale(num_samples, Gst.SECOND, sample_rate)
|
Determine duration of samples using GStreamer helper for precise
math.
|
Determine duration of samples using GStreamer helper for precise
math.
|
[
"Determine",
"duration",
"of",
"samples",
"using",
"GStreamer",
"helper",
"for",
"precise",
"math",
"."
] |
def calculate_duration(num_samples, sample_rate):
"""Determine duration of samples using GStreamer helper for precise
math."""
return Gst.util_uint64_scale(num_samples, Gst.SECOND, sample_rate)
|
[
"def",
"calculate_duration",
"(",
"num_samples",
",",
"sample_rate",
")",
":",
"return",
"Gst",
".",
"util_uint64_scale",
"(",
"num_samples",
",",
"Gst",
".",
"SECOND",
",",
"sample_rate",
")"
] |
https://github.com/mopidy/mopidy/blob/796ebe9b4e1fe7efdb24199cda810492dcb903a1/mopidy/audio/utils.py#L5-L8
|
|
rajarshd/Multi-Step-Reasoning
|
3218d626839f7217554f38d82e00e4f460b508e4
|
msr/reader/model.py
|
python
|
Model.init_optimizer
|
(self, state_dict=None)
|
Initialize an optimizer for the free parameters of the network.
Args:
state_dict: network parameters
|
Initialize an optimizer for the free parameters of the network.
|
[
"Initialize",
"an",
"optimizer",
"for",
"the",
"free",
"parameters",
"of",
"the",
"network",
"."
] |
def init_optimizer(self, state_dict=None):
"""Initialize an optimizer for the free parameters of the network.
Args:
state_dict: network parameters
"""
if self.args.fix_embeddings:
for p in self.network.embedding.parameters():
p.requires_grad = False
parameters = [p for p in self.network.parameters() if p.requires_grad]
if self.multi_step_reasoner is not None:
parameters += [p for p in self.multi_step_reasoner.parameters() if p.requires_grad]
parameters += [p for p in self.reader_self_attn.parameters() if p.requires_grad]
if self.multi_step_reader is not None:
parameters += [p for p in self.multi_step_reader.parameters() if p.requires_grad]
if self.args.optimizer == 'sgd':
self.optimizer = optim.SGD(parameters, self.args.learning_rate,
momentum=self.args.momentum,
weight_decay=self.args.weight_decay)
elif self.args.optimizer == 'adamax':
self.optimizer = optim.Adamax(parameters,
weight_decay=self.args.weight_decay)
else:
raise RuntimeError('Unsupported optimizer: %s' %
self.args.optimizer)
|
[
"def",
"init_optimizer",
"(",
"self",
",",
"state_dict",
"=",
"None",
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":",
"if",
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":",
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"(",
"'Unsupported optimizer: %s'",
"%",
"self",
".",
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] |
https://github.com/rajarshd/Multi-Step-Reasoning/blob/3218d626839f7217554f38d82e00e4f460b508e4/msr/reader/model.py#L225-L251
|
||
tomplus/kubernetes_asyncio
|
f028cc793e3a2c519be6a52a49fb77ff0b014c9b
|
kubernetes_asyncio/client/api/core_v1_api.py
|
python
|
CoreV1Api.list_namespaced_event
|
(self, namespace, **kwargs)
|
return self.list_namespaced_event_with_http_info(namespace, **kwargs)
|
list_namespaced_event # noqa: E501
list or watch objects of kind Event # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.list_namespaced_event(namespace, async_req=True)
>>> result = thread.get()
:param async_req bool: execute request asynchronously
:param str namespace: object name and auth scope, such as for teams and projects (required)
:param str pretty: If 'true', then the output is pretty printed.
:param bool allow_watch_bookmarks: allowWatchBookmarks requests watch events with type \"BOOKMARK\". Servers that do not implement bookmarks may ignore this flag and bookmarks are sent at the server's discretion. Clients should not assume bookmarks are returned at any specific interval, nor may they assume the server will send any BOOKMARK event during a session. If this is not a watch, this field is ignored. If the feature gate WatchBookmarks is not enabled in apiserver, this field is ignored.
:param str _continue: The continue option should be set when retrieving more results from the server. Since this value is server defined, clients may only use the continue value from a previous query result with identical query parameters (except for the value of continue) and the server may reject a continue value it does not recognize. If the specified continue value is no longer valid whether due to expiration (generally five to fifteen minutes) or a configuration change on the server, the server will respond with a 410 ResourceExpired error together with a continue token. If the client needs a consistent list, it must restart their list without the continue field. Otherwise, the client may send another list request with the token received with the 410 error, the server will respond with a list starting from the next key, but from the latest snapshot, which is inconsistent from the previous list results - objects that are created, modified, or deleted after the first list request will be included in the response, as long as their keys are after the \"next key\". This field is not supported when watch is true. Clients may start a watch from the last resourceVersion value returned by the server and not miss any modifications.
:param str field_selector: A selector to restrict the list of returned objects by their fields. Defaults to everything.
:param str label_selector: A selector to restrict the list of returned objects by their labels. Defaults to everything.
:param int limit: limit is a maximum number of responses to return for a list call. If more items exist, the server will set the `continue` field on the list metadata to a value that can be used with the same initial query to retrieve the next set of results. Setting a limit may return fewer than the requested amount of items (up to zero items) in the event all requested objects are filtered out and clients should only use the presence of the continue field to determine whether more results are available. Servers may choose not to support the limit argument and will return all of the available results. If limit is specified and the continue field is empty, clients may assume that no more results are available. This field is not supported if watch is true. The server guarantees that the objects returned when using continue will be identical to issuing a single list call without a limit - that is, no objects created, modified, or deleted after the first request is issued will be included in any subsequent continued requests. This is sometimes referred to as a consistent snapshot, and ensures that a client that is using limit to receive smaller chunks of a very large result can ensure they see all possible objects. If objects are updated during a chunked list the version of the object that was present at the time the first list result was calculated is returned.
:param str resource_version: resourceVersion sets a constraint on what resource versions a request may be served from. See https://kubernetes.io/docs/reference/using-api/api-concepts/#resource-versions for details. Defaults to unset
:param str resource_version_match: resourceVersionMatch determines how resourceVersion is applied to list calls. It is highly recommended that resourceVersionMatch be set for list calls where resourceVersion is set See https://kubernetes.io/docs/reference/using-api/api-concepts/#resource-versions for details. Defaults to unset
:param int timeout_seconds: Timeout for the list/watch call. This limits the duration of the call, regardless of any activity or inactivity.
:param bool watch: Watch for changes to the described resources and return them as a stream of add, update, and remove notifications. Specify resourceVersion.
:param _preload_content: if False, the urllib3.HTTPResponse object will
be returned without reading/decoding response
data. Default is True.
:param _request_timeout: timeout setting for this request. If one
number provided, it will be total request
timeout. It can also be a pair (tuple) of
(connection, read) timeouts.
:return: CoreV1EventList
If the method is called asynchronously,
returns the request thread.
|
list_namespaced_event # noqa: E501
|
[
"list_namespaced_event",
"#",
"noqa",
":",
"E501"
] |
def list_namespaced_event(self, namespace, **kwargs): # noqa: E501
"""list_namespaced_event # noqa: E501
list or watch objects of kind Event # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.list_namespaced_event(namespace, async_req=True)
>>> result = thread.get()
:param async_req bool: execute request asynchronously
:param str namespace: object name and auth scope, such as for teams and projects (required)
:param str pretty: If 'true', then the output is pretty printed.
:param bool allow_watch_bookmarks: allowWatchBookmarks requests watch events with type \"BOOKMARK\". Servers that do not implement bookmarks may ignore this flag and bookmarks are sent at the server's discretion. Clients should not assume bookmarks are returned at any specific interval, nor may they assume the server will send any BOOKMARK event during a session. If this is not a watch, this field is ignored. If the feature gate WatchBookmarks is not enabled in apiserver, this field is ignored.
:param str _continue: The continue option should be set when retrieving more results from the server. Since this value is server defined, clients may only use the continue value from a previous query result with identical query parameters (except for the value of continue) and the server may reject a continue value it does not recognize. If the specified continue value is no longer valid whether due to expiration (generally five to fifteen minutes) or a configuration change on the server, the server will respond with a 410 ResourceExpired error together with a continue token. If the client needs a consistent list, it must restart their list without the continue field. Otherwise, the client may send another list request with the token received with the 410 error, the server will respond with a list starting from the next key, but from the latest snapshot, which is inconsistent from the previous list results - objects that are created, modified, or deleted after the first list request will be included in the response, as long as their keys are after the \"next key\". This field is not supported when watch is true. Clients may start a watch from the last resourceVersion value returned by the server and not miss any modifications.
:param str field_selector: A selector to restrict the list of returned objects by their fields. Defaults to everything.
:param str label_selector: A selector to restrict the list of returned objects by their labels. Defaults to everything.
:param int limit: limit is a maximum number of responses to return for a list call. If more items exist, the server will set the `continue` field on the list metadata to a value that can be used with the same initial query to retrieve the next set of results. Setting a limit may return fewer than the requested amount of items (up to zero items) in the event all requested objects are filtered out and clients should only use the presence of the continue field to determine whether more results are available. Servers may choose not to support the limit argument and will return all of the available results. If limit is specified and the continue field is empty, clients may assume that no more results are available. This field is not supported if watch is true. The server guarantees that the objects returned when using continue will be identical to issuing a single list call without a limit - that is, no objects created, modified, or deleted after the first request is issued will be included in any subsequent continued requests. This is sometimes referred to as a consistent snapshot, and ensures that a client that is using limit to receive smaller chunks of a very large result can ensure they see all possible objects. If objects are updated during a chunked list the version of the object that was present at the time the first list result was calculated is returned.
:param str resource_version: resourceVersion sets a constraint on what resource versions a request may be served from. See https://kubernetes.io/docs/reference/using-api/api-concepts/#resource-versions for details. Defaults to unset
:param str resource_version_match: resourceVersionMatch determines how resourceVersion is applied to list calls. It is highly recommended that resourceVersionMatch be set for list calls where resourceVersion is set See https://kubernetes.io/docs/reference/using-api/api-concepts/#resource-versions for details. Defaults to unset
:param int timeout_seconds: Timeout for the list/watch call. This limits the duration of the call, regardless of any activity or inactivity.
:param bool watch: Watch for changes to the described resources and return them as a stream of add, update, and remove notifications. Specify resourceVersion.
:param _preload_content: if False, the urllib3.HTTPResponse object will
be returned without reading/decoding response
data. Default is True.
:param _request_timeout: timeout setting for this request. If one
number provided, it will be total request
timeout. It can also be a pair (tuple) of
(connection, read) timeouts.
:return: CoreV1EventList
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
return self.list_namespaced_event_with_http_info(namespace, **kwargs)
|
[
"def",
"list_namespaced_event",
"(",
"self",
",",
"namespace",
",",
"*",
"*",
"kwargs",
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":",
"# noqa: E501",
"kwargs",
"[",
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".",
"list_namespaced_event_with_http_info",
"(",
"namespace",
",",
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"*",
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")"
] |
https://github.com/tomplus/kubernetes_asyncio/blob/f028cc793e3a2c519be6a52a49fb77ff0b014c9b/kubernetes_asyncio/client/api/core_v1_api.py#L14898-L14931
|
|
alpacahq/pylivetrader
|
2d9bf97103814409ba8b56a4291f2655c59514ee
|
pylivetrader/algorithm.py
|
python
|
Algorithm.__setattr__
|
(self, name, value)
|
[] |
def __setattr__(self, name, value):
# Reject names that overlap with API method names
if hasattr(self, 'api_methods') and name in self.api_methods:
raise AttributeError(
'Cannot set {} on context object as it is the name of '
'an API method.'.format(name)
)
else:
object.__setattr__(self, name, value)
|
[
"def",
"__setattr__",
"(",
"self",
",",
"name",
",",
"value",
")",
":",
"# Reject names that overlap with API method names",
"if",
"hasattr",
"(",
"self",
",",
"'api_methods'",
")",
"and",
"name",
"in",
"self",
".",
"api_methods",
":",
"raise",
"AttributeError",
"(",
"'Cannot set {} on context object as it is the name of '",
"'an API method.'",
".",
"format",
"(",
"name",
")",
")",
"else",
":",
"object",
".",
"__setattr__",
"(",
"self",
",",
"name",
",",
"value",
")"
] |
https://github.com/alpacahq/pylivetrader/blob/2d9bf97103814409ba8b56a4291f2655c59514ee/pylivetrader/algorithm.py#L96-L104
|
||||
Komodo/KomodoEdit
|
61edab75dce2bdb03943b387b0608ea36f548e8e
|
src/apsw/tools/apswtrace.py
|
python
|
fmtfloat
|
(n, decimals=3, total=None)
|
return s
|
Work around borken python float formatting
|
Work around borken python float formatting
|
[
"Work",
"around",
"borken",
"python",
"float",
"formatting"
] |
def fmtfloat(n, decimals=3, total=None):
"Work around borken python float formatting"
s="%0.*f" % (decimals, n)
if total:
s=(" "*total+s)[-total:]
return s
|
[
"def",
"fmtfloat",
"(",
"n",
",",
"decimals",
"=",
"3",
",",
"total",
"=",
"None",
")",
":",
"s",
"=",
"\"%0.*f\"",
"%",
"(",
"decimals",
",",
"n",
")",
"if",
"total",
":",
"s",
"=",
"(",
"\" \"",
"*",
"total",
"+",
"s",
")",
"[",
"-",
"total",
":",
"]",
"return",
"s"
] |
https://github.com/Komodo/KomodoEdit/blob/61edab75dce2bdb03943b387b0608ea36f548e8e/src/apsw/tools/apswtrace.py#L294-L299
|
|
redhat-imaging/imagefactory
|
176f6e045e1df049d50f33a924653128d5ab8b27
|
imgfac/rest/bottle.py
|
python
|
MultiDict.__len__
|
(self)
|
return len(self.dict)
|
[] |
def __len__(self): return len(self.dict)
|
[
"def",
"__len__",
"(",
"self",
")",
":",
"return",
"len",
"(",
"self",
".",
"dict",
")"
] |
https://github.com/redhat-imaging/imagefactory/blob/176f6e045e1df049d50f33a924653128d5ab8b27/imgfac/rest/bottle.py#L1822-L1822
|
|||
TM0831/Spiders
|
89ba07667a1e729b67f012f2f7cf71034243ad28
|
ProxyPool/crawl.py
|
python
|
Crawler.get_proxies
|
(self, callback)
|
return self.proxies
|
运行各个代理爬虫
:param callback: crawl函数名称
:return:
|
运行各个代理爬虫
:param callback: crawl函数名称
:return:
|
[
"运行各个代理爬虫",
":",
"param",
"callback",
":",
"crawl函数名称",
":",
"return",
":"
] |
def get_proxies(self, callback):
"""
运行各个代理爬虫
:param callback: crawl函数名称
:return:
"""
for proxy in eval("self.{}()".format(callback)):
print("成功获取代理：", proxy)
self.proxies.append(proxy)
return self.proxies
|
[
"def",
"get_proxies",
"(",
"self",
",",
"callback",
")",
":",
"for",
"proxy",
"in",
"eval",
"(",
"\"self.{}()\"",
".",
"format",
"(",
"callback",
")",
")",
":",
"print",
"(",
"\"成功获取代理：\", proxy)",
"",
"",
"",
"self",
".",
"proxies",
".",
"append",
"(",
"proxy",
")",
"return",
"self",
".",
"proxies"
] |
https://github.com/TM0831/Spiders/blob/89ba07667a1e729b67f012f2f7cf71034243ad28/ProxyPool/crawl.py#L33-L42
|
|
openhatch/oh-mainline
|
ce29352a034e1223141dcc2f317030bbc3359a51
|
vendor/packages/Django/django/dispatch/saferef.py
|
python
|
BoundMethodWeakref.__call__
|
(self)
|
return None
|
Return a strong reference to the bound method
If the target cannot be retrieved, then will
return None, otherwise returns a bound instance
method for our object and function.
Note:
You may call this method any number of times,
as it does not invalidate the reference.
|
Return a strong reference to the bound method
|
[
"Return",
"a",
"strong",
"reference",
"to",
"the",
"bound",
"method"
] |
def __call__(self):
"""Return a strong reference to the bound method
If the target cannot be retrieved, then will
return None, otherwise returns a bound instance
method for our object and function.
Note:
You may call this method any number of times,
as it does not invalidate the reference.
"""
target = self.weakSelf()
if target is not None:
function = self.weakFunc()
if function is not None:
return function.__get__(target)
return None
|
[
"def",
"__call__",
"(",
"self",
")",
":",
"target",
"=",
"self",
".",
"weakSelf",
"(",
")",
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"is",
"not",
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":",
"function",
"=",
"self",
".",
"weakFunc",
"(",
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"if",
"function",
"is",
"not",
"None",
":",
"return",
"function",
".",
"__get__",
"(",
"target",
")",
"return",
"None"
] |
https://github.com/openhatch/oh-mainline/blob/ce29352a034e1223141dcc2f317030bbc3359a51/vendor/packages/Django/django/dispatch/saferef.py#L171-L187
|
|
biopython/biopython
|
2dd97e71762af7b046d7f7f8a4f1e38db6b06c86
|
Bio/Phylo/PAML/baseml.py
|
python
|
Baseml._set_rel_paths
|
(self)
|
Make file/directory paths relative to the PWD (PRIVATE).
BASEML requires that all paths specified in the control file be
relative to the directory from which it is called rather than
absolute paths.
|
Make file/directory paths relative to the PWD (PRIVATE).
|
[
"Make",
"file",
"/",
"directory",
"paths",
"relative",
"to",
"the",
"PWD",
"(",
"PRIVATE",
")",
"."
] |
def _set_rel_paths(self):
"""Make file/directory paths relative to the PWD (PRIVATE).
BASEML requires that all paths specified in the control file be
relative to the directory from which it is called rather than
absolute paths.
"""
Paml._set_rel_paths(self)
if self.tree is not None:
self._rel_tree = os.path.relpath(self.tree, self.working_dir)
|
[
"def",
"_set_rel_paths",
"(",
"self",
")",
":",
"Paml",
".",
"_set_rel_paths",
"(",
"self",
")",
"if",
"self",
".",
"tree",
"is",
"not",
"None",
":",
"self",
".",
"_rel_tree",
"=",
"os",
".",
"path",
".",
"relpath",
"(",
"self",
".",
"tree",
",",
"self",
".",
"working_dir",
")"
] |
https://github.com/biopython/biopython/blob/2dd97e71762af7b046d7f7f8a4f1e38db6b06c86/Bio/Phylo/PAML/baseml.py#L154-L163
|
||
plotly/plotly.py
|
cfad7862594b35965c0e000813bd7805e8494a5b
|
packages/python/plotly/plotly/graph_objs/_heatmap.py
|
python
|
Heatmap.text
|
(self)
|
return self["text"]
|
Sets the text elements associated with each z value.
The 'text' property is an array that may be specified as a tuple,
list, numpy array, or pandas Series
Returns
-------
numpy.ndarray
|
Sets the text elements associated with each z value.
The 'text' property is an array that may be specified as a tuple,
list, numpy array, or pandas Series
|
[
"Sets",
"the",
"text",
"elements",
"associated",
"with",
"each",
"z",
"value",
".",
"The",
"text",
"property",
"is",
"an",
"array",
"that",
"may",
"be",
"specified",
"as",
"a",
"tuple",
"list",
"numpy",
"array",
"or",
"pandas",
"Series"
] |
def text(self):
"""
Sets the text elements associated with each z value.
The 'text' property is an array that may be specified as a tuple,
list, numpy array, or pandas Series
Returns
-------
numpy.ndarray
"""
return self["text"]
|
[
"def",
"text",
"(",
"self",
")",
":",
"return",
"self",
"[",
"\"text\"",
"]"
] |
https://github.com/plotly/plotly.py/blob/cfad7862594b35965c0e000813bd7805e8494a5b/packages/python/plotly/plotly/graph_objs/_heatmap.py#L1095-L1106
|
|
cloudera/hue
|
23f02102d4547c17c32bd5ea0eb24e9eadd657a4
|
desktop/core/ext-py/SQLAlchemy-1.3.17/lib/sqlalchemy/sql/elements.py
|
python
|
ColumnElement._uncached_proxy_set
|
(self)
|
return s
|
An 'uncached' version of proxy set.
This is so that we can read annotations from the list of columns
without breaking the caching of the above proxy_set.
|
An 'uncached' version of proxy set.
|
[
"An",
"uncached",
"version",
"of",
"proxy",
"set",
"."
] |
def _uncached_proxy_set(self):
"""An 'uncached' version of proxy set.
This is so that we can read annotations from the list of columns
without breaking the caching of the above proxy_set.
"""
s = util.column_set([self])
for c in self._proxies:
s.update(c._uncached_proxy_set())
return s
|
[
"def",
"_uncached_proxy_set",
"(",
"self",
")",
":",
"s",
"=",
"util",
".",
"column_set",
"(",
"[",
"self",
"]",
")",
"for",
"c",
"in",
"self",
".",
"_proxies",
":",
"s",
".",
"update",
"(",
"c",
".",
"_uncached_proxy_set",
"(",
")",
")",
"return",
"s"
] |
https://github.com/cloudera/hue/blob/23f02102d4547c17c32bd5ea0eb24e9eadd657a4/desktop/core/ext-py/SQLAlchemy-1.3.17/lib/sqlalchemy/sql/elements.py#L798-L808
|
|
CedricGuillemet/Imogen
|
ee417b42747ed5b46cb11b02ef0c3630000085b3
|
bin/Lib/distutils/cmd.py
|
python
|
Command.run_command
|
(self, command)
|
Run some other command: uses the 'run_command()' method of
Distribution, which creates and finalizes the command object if
necessary and then invokes its 'run()' method.
|
Run some other command: uses the 'run_command()' method of
Distribution, which creates and finalizes the command object if
necessary and then invokes its 'run()' method.
|
[
"Run",
"some",
"other",
"command",
":",
"uses",
"the",
"run_command",
"()",
"method",
"of",
"Distribution",
"which",
"creates",
"and",
"finalizes",
"the",
"command",
"object",
"if",
"necessary",
"and",
"then",
"invokes",
"its",
"run",
"()",
"method",
"."
] |
def run_command(self, command):
"""Run some other command: uses the 'run_command()' method of
Distribution, which creates and finalizes the command object if
necessary and then invokes its 'run()' method.
"""
self.distribution.run_command(command)
|
[
"def",
"run_command",
"(",
"self",
",",
"command",
")",
":",
"self",
".",
"distribution",
".",
"run_command",
"(",
"command",
")"
] |
https://github.com/CedricGuillemet/Imogen/blob/ee417b42747ed5b46cb11b02ef0c3630000085b3/bin/Lib/distutils/cmd.py#L308-L313
|
||
xonsh/xonsh
|
b76d6f994f22a4078f602f8b386f4ec280c8461f
|
xonsh/parsers/base.py
|
python
|
BaseParser.p_comma_test
|
(self, p)
|
comma_test : COMMA test
|
comma_test : COMMA test
|
[
"comma_test",
":",
"COMMA",
"test"
] |
def p_comma_test(self, p):
"""comma_test : COMMA test"""
p[0] = [p[2]]
|
[
"def",
"p_comma_test",
"(",
"self",
",",
"p",
")",
":",
"p",
"[",
"0",
"]",
"=",
"[",
"p",
"[",
"2",
"]",
"]"
] |
https://github.com/xonsh/xonsh/blob/b76d6f994f22a4078f602f8b386f4ec280c8461f/xonsh/parsers/base.py#L1515-L1517
|
||
dingjiansw101/RoITransformer_DOTA
|
9125055aed313dde7a68882e9931c9ea58c6f6ab
|
fpn/core/module.py
|
python
|
Module.backward
|
(self, out_grads=None)
|
Backward computation.
Parameters
----------
out_grads : NDArray or list of NDArray, optional
Gradient on the outputs to be propagated back.
This parameter is only needed when bind is called
on outputs that are not a loss function.
|
Backward computation.
|
[
"Backward",
"computation",
"."
] |
def backward(self, out_grads=None):
"""Backward computation.
Parameters
----------
out_grads : NDArray or list of NDArray, optional
Gradient on the outputs to be propagated back.
This parameter is only needed when bind is called
on outputs that are not a loss function.
"""
assert self.binded and self.params_initialized
self._exec_group.backward(out_grads=out_grads)
|
[
"def",
"backward",
"(",
"self",
",",
"out_grads",
"=",
"None",
")",
":",
"assert",
"self",
".",
"binded",
"and",
"self",
".",
"params_initialized",
"self",
".",
"_exec_group",
".",
"backward",
"(",
"out_grads",
"=",
"out_grads",
")"
] |
https://github.com/dingjiansw101/RoITransformer_DOTA/blob/9125055aed313dde7a68882e9931c9ea58c6f6ab/fpn/core/module.py#L553-L564
|
||
jeetsukumaran/DendroPy
|
29fd294bf05d890ebf6a8d576c501e471db27ca1
|
src/dendropy/datamodel/treemodel.py
|
python
|
Node.leaf_iter
|
(self, filter_fn=None)
|
Iterate over all tips or leaves that ultimately descend from this node.
Visits all leaf or tip nodes descended from this node. Nodes can
optionally be filtered by ``filter_fn``: only nodes for which ``filter_fn``
returns |True| when called with the node as an argument are yielded.
Parameters
----------
filter_fn : function object, optional
A function object that takes a |Node| object as an argument
and returns |True| if the |Node| object is to be yielded by
the iterator, or |False| if not. If ``filter_fn`` is |None|
(default), then all nodes visited will be yielded.
Returns
-------
:py:class:`collections.Iterator` [|Node|]
An iterator yielding leaf nodes of the subtree rooted at this node.
|
Iterate over all tips or leaves that ultimately descend from this node.
|
[
"Iterate",
"over",
"all",
"tips",
"or",
"leaves",
"that",
"ultimately",
"descend",
"from",
"this",
"node",
"."
] |
def leaf_iter(self, filter_fn=None):
"""
Iterate over all tips or leaves that ultimately descend from this node.
Visits all leaf or tip nodes descended from this node. Nodes can
optionally be filtered by ``filter_fn``: only nodes for which ``filter_fn``
returns |True| when called with the node as an argument are yielded.
Parameters
----------
filter_fn : function object, optional
A function object that takes a |Node| object as an argument
and returns |True| if the |Node| object is to be yielded by
the iterator, or |False| if not. If ``filter_fn`` is |None|
(default), then all nodes visited will be yielded.
Returns
-------
:py:class:`collections.Iterator` [|Node|]
An iterator yielding leaf nodes of the subtree rooted at this node.
"""
if filter_fn:
ff = lambda x: x.is_leaf() and filter_fn(x) or None
else:
ff = lambda x: x.is_leaf() and x or None
for node in self.postorder_iter(ff):
yield node
|
[
"def",
"leaf_iter",
"(",
"self",
",",
"filter_fn",
"=",
"None",
")",
":",
"if",
"filter_fn",
":",
"ff",
"=",
"lambda",
"x",
":",
"x",
".",
"is_leaf",
"(",
")",
"and",
"filter_fn",
"(",
"x",
")",
"or",
"None",
"else",
":",
"ff",
"=",
"lambda",
"x",
":",
"x",
".",
"is_leaf",
"(",
")",
"and",
"x",
"or",
"None",
"for",
"node",
"in",
"self",
".",
"postorder_iter",
"(",
"ff",
")",
":",
"yield",
"node"
] |
https://github.com/jeetsukumaran/DendroPy/blob/29fd294bf05d890ebf6a8d576c501e471db27ca1/src/dendropy/datamodel/treemodel.py#L1315-L1341
|
||
linxid/Machine_Learning_Study_Path
|
558e82d13237114bbb8152483977806fc0c222af
|
Machine Learning In Action/Chapter5-LogisticRegression/venv/Lib/site-packages/pkg_resources/__init__.py
|
python
|
NullProvider._fn
|
(self, base, resource_name)
|
return base
|
[] |
def _fn(self, base, resource_name):
if resource_name:
return os.path.join(base, *resource_name.split('/'))
return base
|
[
"def",
"_fn",
"(",
"self",
",",
"base",
",",
"resource_name",
")",
":",
"if",
"resource_name",
":",
"return",
"os",
".",
"path",
".",
"join",
"(",
"base",
",",
"*",
"resource_name",
".",
"split",
"(",
"'/'",
")",
")",
"return",
"base"
] |
https://github.com/linxid/Machine_Learning_Study_Path/blob/558e82d13237114bbb8152483977806fc0c222af/Machine Learning In Action/Chapter5-LogisticRegression/venv/Lib/site-packages/pkg_resources/__init__.py#L1551-L1554
|
|||
wxWidgets/Phoenix
|
b2199e299a6ca6d866aa6f3d0888499136ead9d6
|
wx/lib/plot/polyobjects.py
|
python
|
PolyBoxPlot.draw
|
(self, dc, printerScale, coord=None)
|
Draws a box plot on the DC.
Notes
-----
The following draw order is required:
1. First the whisker line
2. Then the IQR box
3. Lasly the median line.
This is because
+ The whiskers are drawn as single line rather than two lines
+ The median line must be visible over the box if the box has a fill.
Other than that, the draw order can be changed.
|
Draws a box plot on the DC.
|
[
"Draws",
"a",
"box",
"plot",
"on",
"the",
"DC",
"."
] |
def draw(self, dc, printerScale, coord=None):
"""
Draws a box plot on the DC.
Notes
-----
The following draw order is required:
1. First the whisker line
2. Then the IQR box
3. Lasly the median line.
This is because
+ The whiskers are drawn as single line rather than two lines
+ The median line must be visible over the box if the box has a fill.
Other than that, the draw order can be changed.
"""
self._draw_whisker(dc, printerScale)
self._draw_iqr_box(dc, printerScale)
self._draw_median(dc, printerScale) # median after box
self._draw_whisker_ends(dc, printerScale)
self._draw_outliers(dc, printerScale)
|
[
"def",
"draw",
"(",
"self",
",",
"dc",
",",
"printerScale",
",",
"coord",
"=",
"None",
")",
":",
"self",
".",
"_draw_whisker",
"(",
"dc",
",",
"printerScale",
")",
"self",
".",
"_draw_iqr_box",
"(",
"dc",
",",
"printerScale",
")",
"self",
".",
"_draw_median",
"(",
"dc",
",",
"printerScale",
")",
"# median after box",
"self",
".",
"_draw_whisker_ends",
"(",
"dc",
",",
"printerScale",
")",
"self",
".",
"_draw_outliers",
"(",
"dc",
",",
"printerScale",
")"
] |
https://github.com/wxWidgets/Phoenix/blob/b2199e299a6ca6d866aa6f3d0888499136ead9d6/wx/lib/plot/polyobjects.py#L1065-L1088
|
||
sentinel-hub/eo-learn
|
cf964eaf173668d6a374675dbd7c1d244264c11d
|
examples/crop-type-classification/Tasks/CropTypeClassTasks.py
|
python
|
FixLPIS._fix_danish_lpis
|
(self, eopatch)
|
See Task's docs for the explanation of what is done.
|
See Task's docs for the explanation of what is done.
|
[
"See",
"Task",
"s",
"docs",
"for",
"the",
"explanation",
"of",
"what",
"is",
"done",
"."
] |
def _fix_danish_lpis(self, eopatch):
"""
See Task's docs for the explanation of what is done.
"""
eopatch.vector_timeless[self.feature].rename(index=str, columns={"CropName": "crop_geopedia_idx"}, inplace=True)
eopatch.vector_timeless[self.feature] = pd.merge(eopatch.vector_timeless[self.feature],
self.mapping,
on='crop_geopedia_idx')
eopatch.vector_timeless[self.feature]['crop_geopedia_idx'] = eopatch.vector_timeless[self.feature]['PreCropName']
self.mapping.rename(index=str, columns={"Crop Name": "PreCrop Name"}, inplace=True)
eopatch.vector_timeless[self.feature] = pd.merge(eopatch.vector_timeless[self.feature],
self.mapping,
on='crop_geopedia_idx')
eopatch.vector_timeless[self.feature].drop(['crop_geopedia_idx', 'PreCropName'], axis=1, inplace=True)
|
[
"def",
"_fix_danish_lpis",
"(",
"self",
",",
"eopatch",
")",
":",
"eopatch",
".",
"vector_timeless",
"[",
"self",
".",
"feature",
"]",
".",
"rename",
"(",
"index",
"=",
"str",
",",
"columns",
"=",
"{",
"\"CropName\"",
":",
"\"crop_geopedia_idx\"",
"}",
",",
"inplace",
"=",
"True",
")",
"eopatch",
".",
"vector_timeless",
"[",
"self",
".",
"feature",
"]",
"=",
"pd",
".",
"merge",
"(",
"eopatch",
".",
"vector_timeless",
"[",
"self",
".",
"feature",
"]",
",",
"self",
".",
"mapping",
",",
"on",
"=",
"'crop_geopedia_idx'",
")",
"eopatch",
".",
"vector_timeless",
"[",
"self",
".",
"feature",
"]",
"[",
"'crop_geopedia_idx'",
"]",
"=",
"eopatch",
".",
"vector_timeless",
"[",
"self",
".",
"feature",
"]",
"[",
"'PreCropName'",
"]",
"self",
".",
"mapping",
".",
"rename",
"(",
"index",
"=",
"str",
",",
"columns",
"=",
"{",
"\"Crop Name\"",
":",
"\"PreCrop Name\"",
"}",
",",
"inplace",
"=",
"True",
")",
"eopatch",
".",
"vector_timeless",
"[",
"self",
".",
"feature",
"]",
"=",
"pd",
".",
"merge",
"(",
"eopatch",
".",
"vector_timeless",
"[",
"self",
".",
"feature",
"]",
",",
"self",
".",
"mapping",
",",
"on",
"=",
"'crop_geopedia_idx'",
")",
"eopatch",
".",
"vector_timeless",
"[",
"self",
".",
"feature",
"]",
".",
"drop",
"(",
"[",
"'crop_geopedia_idx'",
",",
"'PreCropName'",
"]",
",",
"axis",
"=",
"1",
",",
"inplace",
"=",
"True",
")"
] |
https://github.com/sentinel-hub/eo-learn/blob/cf964eaf173668d6a374675dbd7c1d244264c11d/examples/crop-type-classification/Tasks/CropTypeClassTasks.py#L546-L559
|
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