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6,200 | biolink/biolink-model | metamodel/generators/pythongen.py | PythonGenerator.all_slots_for | def all_slots_for(self, cls: ClassDefinition) -> List[SlotDefinitionName]:
""" Return all slots for class cls """
if not cls.is_a:
return cls.slots
else:
return [sn for sn in self.all_slots_for(self.schema.classes[cls.is_a]) if sn not in cls.slot_usage] \
+ cls.slots | python | def all_slots_for(self, cls: ClassDefinition) -> List[SlotDefinitionName]:
""" Return all slots for class cls """
if not cls.is_a:
return cls.slots
else:
return [sn for sn in self.all_slots_for(self.schema.classes[cls.is_a]) if sn not in cls.slot_usage] \
+ cls.slots | ['def', 'all_slots_for', '(', 'self', ',', 'cls', ':', 'ClassDefinition', ')', '->', 'List', '[', 'SlotDefinitionName', ']', ':', 'if', 'not', 'cls', '.', 'is_a', ':', 'return', 'cls', '.', 'slots', 'else', ':', 'return', '[', 'sn', 'for', 'sn', 'in', 'self', '.', 'all_slots_for', '(', 'self', '.', 'schema', '.', 'classes', '[', 'cls', '.', 'is_a', ']', ')', 'if', 'sn', 'not', 'in', 'cls', '.', 'slot_usage', ']', '+', 'cls', '.', 'slots'] | Return all slots for class cls | ['Return', 'all', 'slots', 'for', 'class', 'cls'] | train | https://github.com/biolink/biolink-model/blob/f379e28d5d4085e1115798c6cb28e5acc4dba8b4/metamodel/generators/pythongen.py#L242-L248 |
6,201 | igorcoding/asynctnt-queue | asynctnt_queue/tube.py | Tube.release | async def release(self, task_id, *, delay=None):
"""
Release task (return to queue) with delay if specified
:param task_id: Task id
:param delay: Time in seconds before task will become ready again
:return: Task instance
"""
opts = {}
if delay is not None:
opts['delay'] = delay
args = (task_id, opts)
res = await self.conn.call(self.__funcs['release'], args)
return self._create_task(res.body) | python | async def release(self, task_id, *, delay=None):
"""
Release task (return to queue) with delay if specified
:param task_id: Task id
:param delay: Time in seconds before task will become ready again
:return: Task instance
"""
opts = {}
if delay is not None:
opts['delay'] = delay
args = (task_id, opts)
res = await self.conn.call(self.__funcs['release'], args)
return self._create_task(res.body) | ['async', 'def', 'release', '(', 'self', ',', 'task_id', ',', '*', ',', 'delay', '=', 'None', ')', ':', 'opts', '=', '{', '}', 'if', 'delay', 'is', 'not', 'None', ':', 'opts', '[', "'delay'", ']', '=', 'delay', 'args', '=', '(', 'task_id', ',', 'opts', ')', 'res', '=', 'await', 'self', '.', 'conn', '.', 'call', '(', 'self', '.', '__funcs', '[', "'release'", ']', ',', 'args', ')', 'return', 'self', '.', '_create_task', '(', 'res', '.', 'body', ')'] | Release task (return to queue) with delay if specified
:param task_id: Task id
:param delay: Time in seconds before task will become ready again
:return: Task instance | ['Release', 'task', '(', 'return', 'to', 'queue', ')', 'with', 'delay', 'if', 'specified'] | train | https://github.com/igorcoding/asynctnt-queue/blob/75719b2dd27e8314ae924aea6a7a85be8f48ecc5/asynctnt_queue/tube.py#L141-L154 |
6,202 | bram85/topydo | topydo/lib/Todo.py | Todo.days_till_due | def days_till_due(self):
"""
Returns the number of days till the due date. Returns a negative number
of days when the due date is in the past.
Returns 0 when the task has no due date.
"""
due = self.due_date()
if due:
diff = due - date.today()
return diff.days
return 0 | python | def days_till_due(self):
"""
Returns the number of days till the due date. Returns a negative number
of days when the due date is in the past.
Returns 0 when the task has no due date.
"""
due = self.due_date()
if due:
diff = due - date.today()
return diff.days
return 0 | ['def', 'days_till_due', '(', 'self', ')', ':', 'due', '=', 'self', '.', 'due_date', '(', ')', 'if', 'due', ':', 'diff', '=', 'due', '-', 'date', '.', 'today', '(', ')', 'return', 'diff', '.', 'days', 'return', '0'] | Returns the number of days till the due date. Returns a negative number
of days when the due date is in the past.
Returns 0 when the task has no due date. | ['Returns', 'the', 'number', 'of', 'days', 'till', 'the', 'due', 'date', '.', 'Returns', 'a', 'negative', 'number', 'of', 'days', 'when', 'the', 'due', 'date', 'is', 'in', 'the', 'past', '.', 'Returns', '0', 'when', 'the', 'task', 'has', 'no', 'due', 'date', '.'] | train | https://github.com/bram85/topydo/blob/b59fcfca5361869a6b78d4c9808c7c6cd0a18b58/topydo/lib/Todo.py#L73-L83 |
6,203 | timothyb0912/pylogit | pylogit/base_multinomial_cm_v2.py | check_type_of_param_list_elements | def check_type_of_param_list_elements(param_list):
"""
Ensures that all elements of param_list are ndarrays or None. Raises a
helpful ValueError if otherwise.
"""
try:
assert isinstance(param_list[0], np.ndarray)
assert all([(x is None or isinstance(x, np.ndarray))
for x in param_list])
except AssertionError:
msg = "param_list[0] must be a numpy array."
msg_2 = "All other elements must be numpy arrays or None."
total_msg = msg + "\n" + msg_2
raise TypeError(total_msg)
return None | python | def check_type_of_param_list_elements(param_list):
"""
Ensures that all elements of param_list are ndarrays or None. Raises a
helpful ValueError if otherwise.
"""
try:
assert isinstance(param_list[0], np.ndarray)
assert all([(x is None or isinstance(x, np.ndarray))
for x in param_list])
except AssertionError:
msg = "param_list[0] must be a numpy array."
msg_2 = "All other elements must be numpy arrays or None."
total_msg = msg + "\n" + msg_2
raise TypeError(total_msg)
return None | ['def', 'check_type_of_param_list_elements', '(', 'param_list', ')', ':', 'try', ':', 'assert', 'isinstance', '(', 'param_list', '[', '0', ']', ',', 'np', '.', 'ndarray', ')', 'assert', 'all', '(', '[', '(', 'x', 'is', 'None', 'or', 'isinstance', '(', 'x', ',', 'np', '.', 'ndarray', ')', ')', 'for', 'x', 'in', 'param_list', ']', ')', 'except', 'AssertionError', ':', 'msg', '=', '"param_list[0] must be a numpy array."', 'msg_2', '=', '"All other elements must be numpy arrays or None."', 'total_msg', '=', 'msg', '+', '"\\n"', '+', 'msg_2', 'raise', 'TypeError', '(', 'total_msg', ')', 'return', 'None'] | Ensures that all elements of param_list are ndarrays or None. Raises a
helpful ValueError if otherwise. | ['Ensures', 'that', 'all', 'elements', 'of', 'param_list', 'are', 'ndarrays', 'or', 'None', '.', 'Raises', 'a', 'helpful', 'ValueError', 'if', 'otherwise', '.'] | train | https://github.com/timothyb0912/pylogit/blob/f83b0fd6debaa7358d87c3828428f6d4ead71357/pylogit/base_multinomial_cm_v2.py#L425-L440 |
6,204 | cloudtools/stacker | stacker/dag/__init__.py | DAG.walk | def walk(self, walk_func):
""" Walks each node of the graph in reverse topological order.
This can be used to perform a set of operations, where the next
operation depends on the previous operation. It's important to note
that walking happens serially, and is not paralellized.
Args:
walk_func (:class:`types.FunctionType`): The function to be called
on each node of the graph.
"""
nodes = self.topological_sort()
# Reverse so we start with nodes that have no dependencies.
nodes.reverse()
for n in nodes:
walk_func(n) | python | def walk(self, walk_func):
""" Walks each node of the graph in reverse topological order.
This can be used to perform a set of operations, where the next
operation depends on the previous operation. It's important to note
that walking happens serially, and is not paralellized.
Args:
walk_func (:class:`types.FunctionType`): The function to be called
on each node of the graph.
"""
nodes = self.topological_sort()
# Reverse so we start with nodes that have no dependencies.
nodes.reverse()
for n in nodes:
walk_func(n) | ['def', 'walk', '(', 'self', ',', 'walk_func', ')', ':', 'nodes', '=', 'self', '.', 'topological_sort', '(', ')', '# Reverse so we start with nodes that have no dependencies.', 'nodes', '.', 'reverse', '(', ')', 'for', 'n', 'in', 'nodes', ':', 'walk_func', '(', 'n', ')'] | Walks each node of the graph in reverse topological order.
This can be used to perform a set of operations, where the next
operation depends on the previous operation. It's important to note
that walking happens serially, and is not paralellized.
Args:
walk_func (:class:`types.FunctionType`): The function to be called
on each node of the graph. | ['Walks', 'each', 'node', 'of', 'the', 'graph', 'in', 'reverse', 'topological', 'order', '.', 'This', 'can', 'be', 'used', 'to', 'perform', 'a', 'set', 'of', 'operations', 'where', 'the', 'next', 'operation', 'depends', 'on', 'the', 'previous', 'operation', '.', 'It', 's', 'important', 'to', 'note', 'that', 'walking', 'happens', 'serially', 'and', 'is', 'not', 'paralellized', '.'] | train | https://github.com/cloudtools/stacker/blob/ad6013a03a560c46ba3c63c4d153336273e6da5d/stacker/dag/__init__.py#L152-L167 |
6,205 | django-json-api/django-rest-framework-json-api | rest_framework_json_api/utils.py | _format_object | def _format_object(obj, format_type=None):
"""Depending on settings calls either `format_keys` or `format_field_names`"""
if json_api_settings.FORMAT_KEYS is not None:
return format_keys(obj, format_type)
return format_field_names(obj, format_type) | python | def _format_object(obj, format_type=None):
"""Depending on settings calls either `format_keys` or `format_field_names`"""
if json_api_settings.FORMAT_KEYS is not None:
return format_keys(obj, format_type)
return format_field_names(obj, format_type) | ['def', '_format_object', '(', 'obj', ',', 'format_type', '=', 'None', ')', ':', 'if', 'json_api_settings', '.', 'FORMAT_KEYS', 'is', 'not', 'None', ':', 'return', 'format_keys', '(', 'obj', ',', 'format_type', ')', 'return', 'format_field_names', '(', 'obj', ',', 'format_type', ')'] | Depending on settings calls either `format_keys` or `format_field_names` | ['Depending', 'on', 'settings', 'calls', 'either', 'format_keys', 'or', 'format_field_names'] | train | https://github.com/django-json-api/django-rest-framework-json-api/blob/de7021f9e011615ce8b65d0cb38227c6c12721b6/rest_framework_json_api/utils.py#L121-L127 |
6,206 | LonamiWebs/Telethon | telethon/tl/custom/message.py | Message.edit | async def edit(self, *args, **kwargs):
"""
Edits the message iff it's outgoing. Shorthand for
`telethon.client.messages.MessageMethods.edit_message`
with both ``entity`` and ``message`` already set.
Returns ``None`` if the message was incoming,
or the edited `Message` otherwise.
.. note::
This is different from `client.edit_message
<telethon.client.messages.MessageMethods.edit_message>`
and **will respect** the previous state of the message.
For example, if the message didn't have a link preview,
the edit won't add one by default, and you should force
it by setting it to ``True`` if you want it.
This is generally the most desired and convenient behaviour,
and will work for link previews and message buttons.
"""
if self.fwd_from or not self.out:
return None # We assume self.out was patched for our chat
if 'link_preview' not in kwargs:
kwargs['link_preview'] = bool(self.web_preview)
if 'buttons' not in kwargs:
kwargs['buttons'] = self.reply_markup
return await self._client.edit_message(
await self.get_input_chat(), self.id,
*args, **kwargs
) | python | async def edit(self, *args, **kwargs):
"""
Edits the message iff it's outgoing. Shorthand for
`telethon.client.messages.MessageMethods.edit_message`
with both ``entity`` and ``message`` already set.
Returns ``None`` if the message was incoming,
or the edited `Message` otherwise.
.. note::
This is different from `client.edit_message
<telethon.client.messages.MessageMethods.edit_message>`
and **will respect** the previous state of the message.
For example, if the message didn't have a link preview,
the edit won't add one by default, and you should force
it by setting it to ``True`` if you want it.
This is generally the most desired and convenient behaviour,
and will work for link previews and message buttons.
"""
if self.fwd_from or not self.out:
return None # We assume self.out was patched for our chat
if 'link_preview' not in kwargs:
kwargs['link_preview'] = bool(self.web_preview)
if 'buttons' not in kwargs:
kwargs['buttons'] = self.reply_markup
return await self._client.edit_message(
await self.get_input_chat(), self.id,
*args, **kwargs
) | ['async', 'def', 'edit', '(', 'self', ',', '*', 'args', ',', '*', '*', 'kwargs', ')', ':', 'if', 'self', '.', 'fwd_from', 'or', 'not', 'self', '.', 'out', ':', 'return', 'None', '# We assume self.out was patched for our chat', 'if', "'link_preview'", 'not', 'in', 'kwargs', ':', 'kwargs', '[', "'link_preview'", ']', '=', 'bool', '(', 'self', '.', 'web_preview', ')', 'if', "'buttons'", 'not', 'in', 'kwargs', ':', 'kwargs', '[', "'buttons'", ']', '=', 'self', '.', 'reply_markup', 'return', 'await', 'self', '.', '_client', '.', 'edit_message', '(', 'await', 'self', '.', 'get_input_chat', '(', ')', ',', 'self', '.', 'id', ',', '*', 'args', ',', '*', '*', 'kwargs', ')'] | Edits the message iff it's outgoing. Shorthand for
`telethon.client.messages.MessageMethods.edit_message`
with both ``entity`` and ``message`` already set.
Returns ``None`` if the message was incoming,
or the edited `Message` otherwise.
.. note::
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<telethon.client.messages.MessageMethods.edit_message>`
and **will respect** the previous state of the message.
For example, if the message didn't have a link preview,
the edit won't add one by default, and you should force
it by setting it to ``True`` if you want it.
This is generally the most desired and convenient behaviour,
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6,207 | skioo/django-customer-billing | billing/actions/credit_cards.py | reactivate | def reactivate(credit_card_id: str) -> None:
"""
Reactivates a credit card.
"""
logger.info('reactivating-credit-card', credit_card_id=credit_card_id)
with transaction.atomic():
cc = CreditCard.objects.get(pk=credit_card_id)
cc.reactivate()
cc.save() | python | def reactivate(credit_card_id: str) -> None:
"""
Reactivates a credit card.
"""
logger.info('reactivating-credit-card', credit_card_id=credit_card_id)
with transaction.atomic():
cc = CreditCard.objects.get(pk=credit_card_id)
cc.reactivate()
cc.save() | ['def', 'reactivate', '(', 'credit_card_id', ':', 'str', ')', '->', 'None', ':', 'logger', '.', 'info', '(', "'reactivating-credit-card'", ',', 'credit_card_id', '=', 'credit_card_id', ')', 'with', 'transaction', '.', 'atomic', '(', ')', ':', 'cc', '=', 'CreditCard', '.', 'objects', '.', 'get', '(', 'pk', '=', 'credit_card_id', ')', 'cc', '.', 'reactivate', '(', ')', 'cc', '.', 'save', '(', ')'] | Reactivates a credit card. | ['Reactivates', 'a', 'credit', 'card', '.'] | train | https://github.com/skioo/django-customer-billing/blob/6ac1ed9ef9d1d7eee0379de7f0c4b76919ae1f2d/billing/actions/credit_cards.py#L20-L28 |
6,208 | LuminosoInsight/python-ftfy | ftfy/fixes.py | fix_surrogates | def fix_surrogates(text):
"""
Replace 16-bit surrogate codepoints with the characters they represent
(when properly paired), or with \ufffd otherwise.
>>> high_surrogate = chr(0xd83d)
>>> low_surrogate = chr(0xdca9)
>>> print(fix_surrogates(high_surrogate + low_surrogate))
💩
>>> print(fix_surrogates(low_surrogate + high_surrogate))
��
The above doctest had to be very carefully written, because even putting
the Unicode escapes of the surrogates in the docstring was causing
various tools to fail, which I think just goes to show why this fixer is
necessary.
"""
if SURROGATE_RE.search(text):
text = SURROGATE_PAIR_RE.sub(convert_surrogate_pair, text)
text = SURROGATE_RE.sub('\ufffd', text)
return text | python | def fix_surrogates(text):
"""
Replace 16-bit surrogate codepoints with the characters they represent
(when properly paired), or with \ufffd otherwise.
>>> high_surrogate = chr(0xd83d)
>>> low_surrogate = chr(0xdca9)
>>> print(fix_surrogates(high_surrogate + low_surrogate))
💩
>>> print(fix_surrogates(low_surrogate + high_surrogate))
��
The above doctest had to be very carefully written, because even putting
the Unicode escapes of the surrogates in the docstring was causing
various tools to fail, which I think just goes to show why this fixer is
necessary.
"""
if SURROGATE_RE.search(text):
text = SURROGATE_PAIR_RE.sub(convert_surrogate_pair, text)
text = SURROGATE_RE.sub('\ufffd', text)
return text | ['def', 'fix_surrogates', '(', 'text', ')', ':', 'if', 'SURROGATE_RE', '.', 'search', '(', 'text', ')', ':', 'text', '=', 'SURROGATE_PAIR_RE', '.', 'sub', '(', 'convert_surrogate_pair', ',', 'text', ')', 'text', '=', 'SURROGATE_RE', '.', 'sub', '(', "'\\ufffd'", ',', 'text', ')', 'return', 'text'] | Replace 16-bit surrogate codepoints with the characters they represent
(when properly paired), or with \ufffd otherwise.
>>> high_surrogate = chr(0xd83d)
>>> low_surrogate = chr(0xdca9)
>>> print(fix_surrogates(high_surrogate + low_surrogate))
💩
>>> print(fix_surrogates(low_surrogate + high_surrogate))
��
The above doctest had to be very carefully written, because even putting
the Unicode escapes of the surrogates in the docstring was causing
various tools to fail, which I think just goes to show why this fixer is
necessary. | ['Replace', '16', '-', 'bit', 'surrogate', 'codepoints', 'with', 'the', 'characters', 'they', 'represent', '(', 'when', 'properly', 'paired', ')', 'or', 'with', '\\', 'ufffd', 'otherwise', '.'] | train | https://github.com/LuminosoInsight/python-ftfy/blob/476acc6ad270bffe07f97d4f7cf2139acdc69633/ftfy/fixes.py#L469-L489 |
6,209 | senaite/senaite.core | bika/lims/jsonapi/update.py | Update.require | def require(self, fieldname, allow_blank=False):
"""fieldname is required"""
if self.request.form and fieldname not in self.request.form.keys():
raise Exception("Required field not found in request: %s" % fieldname)
if self.request.form and (not self.request.form[fieldname] or allow_blank):
raise Exception("Required field %s may not have blank value") | python | def require(self, fieldname, allow_blank=False):
"""fieldname is required"""
if self.request.form and fieldname not in self.request.form.keys():
raise Exception("Required field not found in request: %s" % fieldname)
if self.request.form and (not self.request.form[fieldname] or allow_blank):
raise Exception("Required field %s may not have blank value") | ['def', 'require', '(', 'self', ',', 'fieldname', ',', 'allow_blank', '=', 'False', ')', ':', 'if', 'self', '.', 'request', '.', 'form', 'and', 'fieldname', 'not', 'in', 'self', '.', 'request', '.', 'form', '.', 'keys', '(', ')', ':', 'raise', 'Exception', '(', '"Required field not found in request: %s"', '%', 'fieldname', ')', 'if', 'self', '.', 'request', '.', 'form', 'and', '(', 'not', 'self', '.', 'request', '.', 'form', '[', 'fieldname', ']', 'or', 'allow_blank', ')', ':', 'raise', 'Exception', '(', '"Required field %s may not have blank value"', ')'] | fieldname is required | ['fieldname', 'is', 'required'] | train | https://github.com/senaite/senaite.core/blob/7602ce2ea2f9e81eb34e20ce17b98a3e70713f85/bika/lims/jsonapi/update.py#L167-L172 |
6,210 | daviddrysdale/python-phonenumbers | python/phonenumbers/asyoutypeformatter.py | AsYouTypeFormatter._normalize_and_accrue_digits_and_plus_sign | def _normalize_and_accrue_digits_and_plus_sign(self, next_char, remember_position):
"""Accrues digits and the plus sign to
_accrued_input_without_formatting for later use. If next_char contains
a digit in non-ASCII format (e.g. the full-width version of digits),
it is first normalized to the ASCII version. The return value is
next_char itself, or its normalized version, if next_char is a digit
in non-ASCII format. This method assumes its input is either a digit
or the plus sign."""
if next_char == _PLUS_SIGN:
normalized_char = next_char
self._accrued_input_without_formatting += next_char
else:
next_digit = unicode_digit(next_char, -1)
if next_digit != -1:
normalized_char = unicod(next_digit)
else: # pragma no cover
normalized_char = next_char
self._accrued_input_without_formatting += normalized_char
self._national_number += normalized_char
if remember_position:
self._position_to_remember = len(self._accrued_input_without_formatting)
return normalized_char | python | def _normalize_and_accrue_digits_and_plus_sign(self, next_char, remember_position):
"""Accrues digits and the plus sign to
_accrued_input_without_formatting for later use. If next_char contains
a digit in non-ASCII format (e.g. the full-width version of digits),
it is first normalized to the ASCII version. The return value is
next_char itself, or its normalized version, if next_char is a digit
in non-ASCII format. This method assumes its input is either a digit
or the plus sign."""
if next_char == _PLUS_SIGN:
normalized_char = next_char
self._accrued_input_without_formatting += next_char
else:
next_digit = unicode_digit(next_char, -1)
if next_digit != -1:
normalized_char = unicod(next_digit)
else: # pragma no cover
normalized_char = next_char
self._accrued_input_without_formatting += normalized_char
self._national_number += normalized_char
if remember_position:
self._position_to_remember = len(self._accrued_input_without_formatting)
return normalized_char | ['def', '_normalize_and_accrue_digits_and_plus_sign', '(', 'self', ',', 'next_char', ',', 'remember_position', ')', ':', 'if', 'next_char', '==', '_PLUS_SIGN', ':', 'normalized_char', '=', 'next_char', 'self', '.', '_accrued_input_without_formatting', '+=', 'next_char', 'else', ':', 'next_digit', '=', 'unicode_digit', '(', 'next_char', ',', '-', '1', ')', 'if', 'next_digit', '!=', '-', '1', ':', 'normalized_char', '=', 'unicod', '(', 'next_digit', ')', 'else', ':', '# pragma no cover', 'normalized_char', '=', 'next_char', 'self', '.', '_accrued_input_without_formatting', '+=', 'normalized_char', 'self', '.', '_national_number', '+=', 'normalized_char', 'if', 'remember_position', ':', 'self', '.', '_position_to_remember', '=', 'len', '(', 'self', '.', '_accrued_input_without_formatting', ')', 'return', 'normalized_char'] | Accrues digits and the plus sign to
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it is first normalized to the ASCII version. The return value is
next_char itself, or its normalized version, if next_char is a digit
in non-ASCII format. This method assumes its input is either a digit
or the plus sign. | ['Accrues', 'digits', 'and', 'the', 'plus', 'sign', 'to', '_accrued_input_without_formatting', 'for', 'later', 'use', '.', 'If', 'next_char', 'contains', 'a', 'digit', 'in', 'non', '-', 'ASCII', 'format', '(', 'e', '.', 'g', '.', 'the', 'full', '-', 'width', 'version', 'of', 'digits', ')', 'it', 'is', 'first', 'normalized', 'to', 'the', 'ASCII', 'version', '.', 'The', 'return', 'value', 'is', 'next_char', 'itself', 'or', 'its', 'normalized', 'version', 'if', 'next_char', 'is', 'a', 'digit', 'in', 'non', '-', 'ASCII', 'format', '.', 'This', 'method', 'assumes', 'its', 'input', 'is', 'either', 'a', 'digit', 'or', 'the', 'plus', 'sign', '.'] | train | https://github.com/daviddrysdale/python-phonenumbers/blob/9cc5bb4ab5e661e70789b4c64bf7a9383c7bdc20/python/phonenumbers/asyoutypeformatter.py#L550-L571 |
6,211 | wonambi-python/wonambi | wonambi/trans/filter.py | filter_ | def filter_(data, axis='time', low_cut=None, high_cut=None, order=4,
ftype='butter', Rs=None, notchfreq=50, notchquality=25):
"""Design filter and apply it.
Parameters
----------
ftype : str
'butter', 'cheby1', 'cheby2', 'ellip', 'bessel', 'diff', or 'notch'
axis : str, optional
axis to apply the filter on.
low_cut : float, optional
(not for notch) low cutoff for high-pass filter
high_cut : float, optional
(not for notch) high cutoff for low-pass filter
order : int, optional
(not for notch) filter order
data : instance of Data
(not for notch) the data to filter.
notchfreq : float
(only for notch) frequency to apply notch filter to (+ harmonics)
notchquality : int
(only for notch) Quality factor (see scipy.signal.iirnotch)
Returns
-------
filtered_data : instance of DataRaw
filtered data
Notes
-----
You can specify any filter type as defined by iirfilter.
If you specify low_cut only, it generates a high-pass filter.
If you specify high_cut only, it generates a low-pass filter.
If you specify both, it generates a band-pass filter.
low_cut and high_cut should be given as ratio of the Nyquist. But if you
specify s_freq, then the ratio will be computed automatically.
Raises
------
ValueError
if the cutoff frequency is larger than the Nyquist frequency.
"""
nyquist = data.s_freq / 2.
btype = None
if low_cut is not None and high_cut is not None:
if low_cut > nyquist or high_cut > nyquist:
raise ValueError('cutoff has to be less than Nyquist '
'frequency')
btype = 'bandpass'
Wn = (low_cut / nyquist,
high_cut / nyquist)
elif low_cut is not None:
if low_cut > nyquist:
raise ValueError('cutoff has to be less than Nyquist '
'frequency')
btype = 'highpass'
Wn = low_cut / nyquist
elif high_cut is not None:
if high_cut > nyquist:
raise ValueError('cutoff has to be less than Nyquist '
'frequency')
btype = 'lowpass'
Wn = high_cut / nyquist
if btype is None and ftype != 'notch':
raise TypeError('You should specify at least low_cut or high_cut')
if Rs is None:
Rs = 40
if ftype == 'notch':
b_a = [iirnotch(w0 / nyquist, notchquality) for w0 in arange(notchfreq, nyquist, notchfreq)]
else:
lg.debug('order {0: 2}, Wn {1}, btype {2}, ftype {3}'
''.format(order, str(Wn), btype, ftype))
b_a = [iirfilter(order, Wn, btype=btype, ftype=ftype, rs=Rs), ]
fdata = data._copy()
for i in range(data.number_of('trial')):
x = data.data[i]
for b, a in b_a:
x = filtfilt(b, a, x, axis=data.index_of(axis))
fdata.data[i] = x
return fdata | python | def filter_(data, axis='time', low_cut=None, high_cut=None, order=4,
ftype='butter', Rs=None, notchfreq=50, notchquality=25):
"""Design filter and apply it.
Parameters
----------
ftype : str
'butter', 'cheby1', 'cheby2', 'ellip', 'bessel', 'diff', or 'notch'
axis : str, optional
axis to apply the filter on.
low_cut : float, optional
(not for notch) low cutoff for high-pass filter
high_cut : float, optional
(not for notch) high cutoff for low-pass filter
order : int, optional
(not for notch) filter order
data : instance of Data
(not for notch) the data to filter.
notchfreq : float
(only for notch) frequency to apply notch filter to (+ harmonics)
notchquality : int
(only for notch) Quality factor (see scipy.signal.iirnotch)
Returns
-------
filtered_data : instance of DataRaw
filtered data
Notes
-----
You can specify any filter type as defined by iirfilter.
If you specify low_cut only, it generates a high-pass filter.
If you specify high_cut only, it generates a low-pass filter.
If you specify both, it generates a band-pass filter.
low_cut and high_cut should be given as ratio of the Nyquist. But if you
specify s_freq, then the ratio will be computed automatically.
Raises
------
ValueError
if the cutoff frequency is larger than the Nyquist frequency.
"""
nyquist = data.s_freq / 2.
btype = None
if low_cut is not None and high_cut is not None:
if low_cut > nyquist or high_cut > nyquist:
raise ValueError('cutoff has to be less than Nyquist '
'frequency')
btype = 'bandpass'
Wn = (low_cut / nyquist,
high_cut / nyquist)
elif low_cut is not None:
if low_cut > nyquist:
raise ValueError('cutoff has to be less than Nyquist '
'frequency')
btype = 'highpass'
Wn = low_cut / nyquist
elif high_cut is not None:
if high_cut > nyquist:
raise ValueError('cutoff has to be less than Nyquist '
'frequency')
btype = 'lowpass'
Wn = high_cut / nyquist
if btype is None and ftype != 'notch':
raise TypeError('You should specify at least low_cut or high_cut')
if Rs is None:
Rs = 40
if ftype == 'notch':
b_a = [iirnotch(w0 / nyquist, notchquality) for w0 in arange(notchfreq, nyquist, notchfreq)]
else:
lg.debug('order {0: 2}, Wn {1}, btype {2}, ftype {3}'
''.format(order, str(Wn), btype, ftype))
b_a = [iirfilter(order, Wn, btype=btype, ftype=ftype, rs=Rs), ]
fdata = data._copy()
for i in range(data.number_of('trial')):
x = data.data[i]
for b, a in b_a:
x = filtfilt(b, a, x, axis=data.index_of(axis))
fdata.data[i] = x
return fdata | ['def', 'filter_', '(', 'data', ',', 'axis', '=', "'time'", ',', 'low_cut', '=', 'None', ',', 'high_cut', '=', 'None', ',', 'order', '=', '4', ',', 'ftype', '=', "'butter'", ',', 'Rs', '=', 'None', ',', 'notchfreq', '=', '50', ',', 'notchquality', '=', '25', ')', ':', 'nyquist', '=', 'data', '.', 's_freq', '/', '2.', 'btype', '=', 'None', 'if', 'low_cut', 'is', 'not', 'None', 'and', 'high_cut', 'is', 'not', 'None', ':', 'if', 'low_cut', '>', 'nyquist', 'or', 'high_cut', '>', 'nyquist', ':', 'raise', 'ValueError', '(', "'cutoff has to be less than Nyquist '", "'frequency'", ')', 'btype', '=', "'bandpass'", 'Wn', '=', '(', 'low_cut', '/', 'nyquist', ',', 'high_cut', '/', 'nyquist', ')', 'elif', 'low_cut', 'is', 'not', 'None', ':', 'if', 'low_cut', '>', 'nyquist', ':', 'raise', 'ValueError', '(', "'cutoff has to be less than Nyquist '", "'frequency'", ')', 'btype', '=', "'highpass'", 'Wn', '=', 'low_cut', '/', 'nyquist', 'elif', 'high_cut', 'is', 'not', 'None', ':', 'if', 'high_cut', '>', 'nyquist', ':', 'raise', 'ValueError', '(', "'cutoff has to be less than Nyquist '", "'frequency'", ')', 'btype', '=', "'lowpass'", 'Wn', '=', 'high_cut', '/', 'nyquist', 'if', 'btype', 'is', 'None', 'and', 'ftype', '!=', "'notch'", ':', 'raise', 'TypeError', '(', "'You should specify at least low_cut or high_cut'", ')', 'if', 'Rs', 'is', 'None', ':', 'Rs', '=', '40', 'if', 'ftype', '==', "'notch'", ':', 'b_a', '=', '[', 'iirnotch', '(', 'w0', '/', 'nyquist', ',', 'notchquality', ')', 'for', 'w0', 'in', 'arange', '(', 'notchfreq', ',', 'nyquist', ',', 'notchfreq', ')', ']', 'else', ':', 'lg', '.', 'debug', '(', "'order {0: 2}, Wn {1}, btype {2}, ftype {3}'", "''", '.', 'format', '(', 'order', ',', 'str', '(', 'Wn', ')', ',', 'btype', ',', 'ftype', ')', ')', 'b_a', '=', '[', 'iirfilter', '(', 'order', ',', 'Wn', ',', 'btype', '=', 'btype', ',', 'ftype', '=', 'ftype', ',', 'rs', '=', 'Rs', ')', ',', ']', 'fdata', '=', 'data', '.', '_copy', '(', ')', 'for', 'i', 'in', 'range', '(', 'data', '.', 'number_of', '(', "'trial'", ')', ')', ':', 'x', '=', 'data', '.', 'data', '[', 'i', ']', 'for', 'b', ',', 'a', 'in', 'b_a', ':', 'x', '=', 'filtfilt', '(', 'b', ',', 'a', ',', 'x', ',', 'axis', '=', 'data', '.', 'index_of', '(', 'axis', ')', ')', 'fdata', '.', 'data', '[', 'i', ']', '=', 'x', 'return', 'fdata'] | Design filter and apply it.
Parameters
----------
ftype : str
'butter', 'cheby1', 'cheby2', 'ellip', 'bessel', 'diff', or 'notch'
axis : str, optional
axis to apply the filter on.
low_cut : float, optional
(not for notch) low cutoff for high-pass filter
high_cut : float, optional
(not for notch) high cutoff for low-pass filter
order : int, optional
(not for notch) filter order
data : instance of Data
(not for notch) the data to filter.
notchfreq : float
(only for notch) frequency to apply notch filter to (+ harmonics)
notchquality : int
(only for notch) Quality factor (see scipy.signal.iirnotch)
Returns
-------
filtered_data : instance of DataRaw
filtered data
Notes
-----
You can specify any filter type as defined by iirfilter.
If you specify low_cut only, it generates a high-pass filter.
If you specify high_cut only, it generates a low-pass filter.
If you specify both, it generates a band-pass filter.
low_cut and high_cut should be given as ratio of the Nyquist. But if you
specify s_freq, then the ratio will be computed automatically.
Raises
------
ValueError
if the cutoff frequency is larger than the Nyquist frequency. | ['Design', 'filter', 'and', 'apply', 'it', '.'] | train | https://github.com/wonambi-python/wonambi/blob/1d8e3d7e53df8017c199f703bcab582914676e76/wonambi/trans/filter.py#L18-L108 |
6,212 | quantopian/zipline | zipline/pipeline/data/dataset.py | DataSetFamily.slice | def slice(cls, *args, **kwargs):
"""Take a slice of a DataSetFamily to produce a dataset
indexed by asset and date.
Parameters
----------
*args
**kwargs
The coordinates to fix along each extra dimension.
Returns
-------
dataset : DataSet
A regular pipeline dataset indexed by asset and date.
Notes
-----
The extra dimensions coords used to produce the result are available
under the ``extra_coords`` attribute.
"""
coords, hash_key = cls._canonical_key(args, kwargs)
try:
return cls._slice_cache[hash_key]
except KeyError:
pass
Slice = cls._make_dataset(coords)
cls._slice_cache[hash_key] = Slice
return Slice | python | def slice(cls, *args, **kwargs):
"""Take a slice of a DataSetFamily to produce a dataset
indexed by asset and date.
Parameters
----------
*args
**kwargs
The coordinates to fix along each extra dimension.
Returns
-------
dataset : DataSet
A regular pipeline dataset indexed by asset and date.
Notes
-----
The extra dimensions coords used to produce the result are available
under the ``extra_coords`` attribute.
"""
coords, hash_key = cls._canonical_key(args, kwargs)
try:
return cls._slice_cache[hash_key]
except KeyError:
pass
Slice = cls._make_dataset(coords)
cls._slice_cache[hash_key] = Slice
return Slice | ['def', 'slice', '(', 'cls', ',', '*', 'args', ',', '*', '*', 'kwargs', ')', ':', 'coords', ',', 'hash_key', '=', 'cls', '.', '_canonical_key', '(', 'args', ',', 'kwargs', ')', 'try', ':', 'return', 'cls', '.', '_slice_cache', '[', 'hash_key', ']', 'except', 'KeyError', ':', 'pass', 'Slice', '=', 'cls', '.', '_make_dataset', '(', 'coords', ')', 'cls', '.', '_slice_cache', '[', 'hash_key', ']', '=', 'Slice', 'return', 'Slice'] | Take a slice of a DataSetFamily to produce a dataset
indexed by asset and date.
Parameters
----------
*args
**kwargs
The coordinates to fix along each extra dimension.
Returns
-------
dataset : DataSet
A regular pipeline dataset indexed by asset and date.
Notes
-----
The extra dimensions coords used to produce the result are available
under the ``extra_coords`` attribute. | ['Take', 'a', 'slice', 'of', 'a', 'DataSetFamily', 'to', 'produce', 'a', 'dataset', 'indexed', 'by', 'asset', 'and', 'date', '.'] | train | https://github.com/quantopian/zipline/blob/77ad15e6dc4c1cbcdc133653bac8a63fc704f7fe/zipline/pipeline/data/dataset.py#L826-L854 |
6,213 | DataONEorg/d1_python | gmn/src/d1_gmn/app/sysmeta_extract.py | assert_invalid_field_list | def assert_invalid_field_list(field_list):
"""raise d1_common.types.exceptions.InvalidRequest() if ``field_list`` contains any
invalid field names. A list of the invalid fields is included in the exception.
- Implicitly called by ``extract_values()``.
"""
if field_list is not None:
invalid_field_list = [
v for v in field_list if v not in get_valid_field_name_list()
]
if invalid_field_list:
raise d1_common.types.exceptions.InvalidRequest(
0, "Invalid fields: {}".format(", ".join(invalid_field_list))
) | python | def assert_invalid_field_list(field_list):
"""raise d1_common.types.exceptions.InvalidRequest() if ``field_list`` contains any
invalid field names. A list of the invalid fields is included in the exception.
- Implicitly called by ``extract_values()``.
"""
if field_list is not None:
invalid_field_list = [
v for v in field_list if v not in get_valid_field_name_list()
]
if invalid_field_list:
raise d1_common.types.exceptions.InvalidRequest(
0, "Invalid fields: {}".format(", ".join(invalid_field_list))
) | ['def', 'assert_invalid_field_list', '(', 'field_list', ')', ':', 'if', 'field_list', 'is', 'not', 'None', ':', 'invalid_field_list', '=', '[', 'v', 'for', 'v', 'in', 'field_list', 'if', 'v', 'not', 'in', 'get_valid_field_name_list', '(', ')', ']', 'if', 'invalid_field_list', ':', 'raise', 'd1_common', '.', 'types', '.', 'exceptions', '.', 'InvalidRequest', '(', '0', ',', '"Invalid fields: {}"', '.', 'format', '(', '", "', '.', 'join', '(', 'invalid_field_list', ')', ')', ')'] | raise d1_common.types.exceptions.InvalidRequest() if ``field_list`` contains any
invalid field names. A list of the invalid fields is included in the exception.
- Implicitly called by ``extract_values()``. | ['raise', 'd1_common', '.', 'types', '.', 'exceptions', '.', 'InvalidRequest', '()', 'if', 'field_list', 'contains', 'any', 'invalid', 'field', 'names', '.', 'A', 'list', 'of', 'the', 'invalid', 'fields', 'is', 'included', 'in', 'the', 'exception', '.'] | train | https://github.com/DataONEorg/d1_python/blob/3ac4d4f3ca052d3e8641a6a329cab526c8ddcb0d/gmn/src/d1_gmn/app/sysmeta_extract.py#L130-L144 |
6,214 | awslabs/aws-sam-cli | samcli/local/docker/lambda_build_container.py | LambdaBuildContainer._convert_to_container_dirs | def _convert_to_container_dirs(host_paths_to_convert, host_to_container_path_mapping):
"""
Use this method to convert a list of host paths to a list of equivalent paths within the container
where the given host path is mounted. This is necessary when SAM CLI needs to pass path information to
the Lambda Builder running within the container.
If a host path is not mounted within the container, then this method simply passes the path to the result
without any changes.
Ex:
[ "/home/foo", "/home/bar", "/home/not/mounted"] => ["/tmp/source", "/tmp/manifest", "/home/not/mounted"]
Parameters
----------
host_paths_to_convert : list
List of paths in host that needs to be converted
host_to_container_path_mapping : dict
Mapping of paths in host to the equivalent paths within the container
Returns
-------
list
Equivalent paths within the container
"""
if not host_paths_to_convert:
# Nothing to do
return host_paths_to_convert
# Make sure the key is absolute host path. Relative paths are tricky to work with because two different
# relative paths can point to the same directory ("../foo", "../../foo")
mapping = {str(pathlib.Path(p).resolve()): v for p, v in host_to_container_path_mapping.items()}
result = []
for original_path in host_paths_to_convert:
abspath = str(pathlib.Path(original_path).resolve())
if abspath in mapping:
result.append(mapping[abspath])
else:
result.append(original_path)
LOG.debug("Cannot convert host path '%s' to its equivalent path within the container. "
"Host path is not mounted within the container", abspath)
return result | python | def _convert_to_container_dirs(host_paths_to_convert, host_to_container_path_mapping):
"""
Use this method to convert a list of host paths to a list of equivalent paths within the container
where the given host path is mounted. This is necessary when SAM CLI needs to pass path information to
the Lambda Builder running within the container.
If a host path is not mounted within the container, then this method simply passes the path to the result
without any changes.
Ex:
[ "/home/foo", "/home/bar", "/home/not/mounted"] => ["/tmp/source", "/tmp/manifest", "/home/not/mounted"]
Parameters
----------
host_paths_to_convert : list
List of paths in host that needs to be converted
host_to_container_path_mapping : dict
Mapping of paths in host to the equivalent paths within the container
Returns
-------
list
Equivalent paths within the container
"""
if not host_paths_to_convert:
# Nothing to do
return host_paths_to_convert
# Make sure the key is absolute host path. Relative paths are tricky to work with because two different
# relative paths can point to the same directory ("../foo", "../../foo")
mapping = {str(pathlib.Path(p).resolve()): v for p, v in host_to_container_path_mapping.items()}
result = []
for original_path in host_paths_to_convert:
abspath = str(pathlib.Path(original_path).resolve())
if abspath in mapping:
result.append(mapping[abspath])
else:
result.append(original_path)
LOG.debug("Cannot convert host path '%s' to its equivalent path within the container. "
"Host path is not mounted within the container", abspath)
return result | ['def', '_convert_to_container_dirs', '(', 'host_paths_to_convert', ',', 'host_to_container_path_mapping', ')', ':', 'if', 'not', 'host_paths_to_convert', ':', '# Nothing to do', 'return', 'host_paths_to_convert', '# Make sure the key is absolute host path. Relative paths are tricky to work with because two different', '# relative paths can point to the same directory ("../foo", "../../foo")', 'mapping', '=', '{', 'str', '(', 'pathlib', '.', 'Path', '(', 'p', ')', '.', 'resolve', '(', ')', ')', ':', 'v', 'for', 'p', ',', 'v', 'in', 'host_to_container_path_mapping', '.', 'items', '(', ')', '}', 'result', '=', '[', ']', 'for', 'original_path', 'in', 'host_paths_to_convert', ':', 'abspath', '=', 'str', '(', 'pathlib', '.', 'Path', '(', 'original_path', ')', '.', 'resolve', '(', ')', ')', 'if', 'abspath', 'in', 'mapping', ':', 'result', '.', 'append', '(', 'mapping', '[', 'abspath', ']', ')', 'else', ':', 'result', '.', 'append', '(', 'original_path', ')', 'LOG', '.', 'debug', '(', '"Cannot convert host path \'%s\' to its equivalent path within the container. "', '"Host path is not mounted within the container"', ',', 'abspath', ')', 'return', 'result'] | Use this method to convert a list of host paths to a list of equivalent paths within the container
where the given host path is mounted. This is necessary when SAM CLI needs to pass path information to
the Lambda Builder running within the container.
If a host path is not mounted within the container, then this method simply passes the path to the result
without any changes.
Ex:
[ "/home/foo", "/home/bar", "/home/not/mounted"] => ["/tmp/source", "/tmp/manifest", "/home/not/mounted"]
Parameters
----------
host_paths_to_convert : list
List of paths in host that needs to be converted
host_to_container_path_mapping : dict
Mapping of paths in host to the equivalent paths within the container
Returns
-------
list
Equivalent paths within the container | ['Use', 'this', 'method', 'to', 'convert', 'a', 'list', 'of', 'host', 'paths', 'to', 'a', 'list', 'of', 'equivalent', 'paths', 'within', 'the', 'container', 'where', 'the', 'given', 'host', 'path', 'is', 'mounted', '.', 'This', 'is', 'necessary', 'when', 'SAM', 'CLI', 'needs', 'to', 'pass', 'path', 'information', 'to', 'the', 'Lambda', 'Builder', 'running', 'within', 'the', 'container', '.'] | train | https://github.com/awslabs/aws-sam-cli/blob/c05af5e7378c6f05f7d82ad3f0bca17204177db6/samcli/local/docker/lambda_build_container.py#L183-L228 |
6,215 | ConsenSys/mythril-classic | mythril/analysis/modules/delegatecall.py | _analyze_states | def _analyze_states(state: GlobalState) -> List[Issue]:
"""
:param state: the current state
:return: returns the issues for that corresponding state
"""
call = get_call_from_state(state)
if call is None:
return []
issues = [] # type: List[Issue]
if call.type is not "DELEGATECALL":
return []
if state.environment.active_function_name is not "fallback":
return []
state = call.state
address = state.get_current_instruction()["address"]
meminstart = get_variable(state.mstate.stack[-3])
if meminstart.type == VarType.CONCRETE:
issues += _concrete_call(call, state, address, meminstart)
return issues | python | def _analyze_states(state: GlobalState) -> List[Issue]:
"""
:param state: the current state
:return: returns the issues for that corresponding state
"""
call = get_call_from_state(state)
if call is None:
return []
issues = [] # type: List[Issue]
if call.type is not "DELEGATECALL":
return []
if state.environment.active_function_name is not "fallback":
return []
state = call.state
address = state.get_current_instruction()["address"]
meminstart = get_variable(state.mstate.stack[-3])
if meminstart.type == VarType.CONCRETE:
issues += _concrete_call(call, state, address, meminstart)
return issues | ['def', '_analyze_states', '(', 'state', ':', 'GlobalState', ')', '->', 'List', '[', 'Issue', ']', ':', 'call', '=', 'get_call_from_state', '(', 'state', ')', 'if', 'call', 'is', 'None', ':', 'return', '[', ']', 'issues', '=', '[', ']', '# type: List[Issue]', 'if', 'call', '.', 'type', 'is', 'not', '"DELEGATECALL"', ':', 'return', '[', ']', 'if', 'state', '.', 'environment', '.', 'active_function_name', 'is', 'not', '"fallback"', ':', 'return', '[', ']', 'state', '=', 'call', '.', 'state', 'address', '=', 'state', '.', 'get_current_instruction', '(', ')', '[', '"address"', ']', 'meminstart', '=', 'get_variable', '(', 'state', '.', 'mstate', '.', 'stack', '[', '-', '3', ']', ')', 'if', 'meminstart', '.', 'type', '==', 'VarType', '.', 'CONCRETE', ':', 'issues', '+=', '_concrete_call', '(', 'call', ',', 'state', ',', 'address', ',', 'meminstart', ')', 'return', 'issues'] | :param state: the current state
:return: returns the issues for that corresponding state | [':', 'param', 'state', ':', 'the', 'current', 'state', ':', 'return', ':', 'returns', 'the', 'issues', 'for', 'that', 'corresponding', 'state'] | train | https://github.com/ConsenSys/mythril-classic/blob/27af71c34b2ce94f4fae5613ec457f93df1a8f56/mythril/analysis/modules/delegatecall.py#L41-L63 |
6,216 | SheffieldML/GPy | GPy/util/netpbmfile.py | NetpbmFile._header | def _header(self, pam=False):
"""Return file header as byte string."""
if pam or self.magicnum == b'P7':
header = "\n".join((
"P7",
"HEIGHT %i" % self.height,
"WIDTH %i" % self.width,
"DEPTH %i" % self.depth,
"MAXVAL %i" % self.maxval,
"\n".join("TUPLTYPE %s" % unicode(i) for i in self.tupltypes),
"ENDHDR\n"))
elif self.maxval == 1:
header = "P4 %i %i\n" % (self.width, self.height)
elif self.depth == 1:
header = "P5 %i %i %i\n" % (self.width, self.height, self.maxval)
else:
header = "P6 %i %i %i\n" % (self.width, self.height, self.maxval)
if sys.version_info[0] > 2:
header = bytes(header, 'ascii')
return header | python | def _header(self, pam=False):
"""Return file header as byte string."""
if pam or self.magicnum == b'P7':
header = "\n".join((
"P7",
"HEIGHT %i" % self.height,
"WIDTH %i" % self.width,
"DEPTH %i" % self.depth,
"MAXVAL %i" % self.maxval,
"\n".join("TUPLTYPE %s" % unicode(i) for i in self.tupltypes),
"ENDHDR\n"))
elif self.maxval == 1:
header = "P4 %i %i\n" % (self.width, self.height)
elif self.depth == 1:
header = "P5 %i %i %i\n" % (self.width, self.height, self.maxval)
else:
header = "P6 %i %i %i\n" % (self.width, self.height, self.maxval)
if sys.version_info[0] > 2:
header = bytes(header, 'ascii')
return header | ['def', '_header', '(', 'self', ',', 'pam', '=', 'False', ')', ':', 'if', 'pam', 'or', 'self', '.', 'magicnum', '==', "b'P7'", ':', 'header', '=', '"\\n"', '.', 'join', '(', '(', '"P7"', ',', '"HEIGHT %i"', '%', 'self', '.', 'height', ',', '"WIDTH %i"', '%', 'self', '.', 'width', ',', '"DEPTH %i"', '%', 'self', '.', 'depth', ',', '"MAXVAL %i"', '%', 'self', '.', 'maxval', ',', '"\\n"', '.', 'join', '(', '"TUPLTYPE %s"', '%', 'unicode', '(', 'i', ')', 'for', 'i', 'in', 'self', '.', 'tupltypes', ')', ',', '"ENDHDR\\n"', ')', ')', 'elif', 'self', '.', 'maxval', '==', '1', ':', 'header', '=', '"P4 %i %i\\n"', '%', '(', 'self', '.', 'width', ',', 'self', '.', 'height', ')', 'elif', 'self', '.', 'depth', '==', '1', ':', 'header', '=', '"P5 %i %i %i\\n"', '%', '(', 'self', '.', 'width', ',', 'self', '.', 'height', ',', 'self', '.', 'maxval', ')', 'else', ':', 'header', '=', '"P6 %i %i %i\\n"', '%', '(', 'self', '.', 'width', ',', 'self', '.', 'height', ',', 'self', '.', 'maxval', ')', 'if', 'sys', '.', 'version_info', '[', '0', ']', '>', '2', ':', 'header', '=', 'bytes', '(', 'header', ',', "'ascii'", ')', 'return', 'header'] | Return file header as byte string. | ['Return', 'file', 'header', 'as', 'byte', 'string', '.'] | train | https://github.com/SheffieldML/GPy/blob/54c32d79d289d622fb18b898aee65a2a431d90cf/GPy/util/netpbmfile.py#L274-L293 |
6,217 | binux/pyspider | pyspider/run.py | processor | def processor(ctx, processor_cls, process_time_limit, enable_stdout_capture=True, get_object=False):
"""
Run Processor.
"""
g = ctx.obj
Processor = load_cls(None, None, processor_cls)
processor = Processor(projectdb=g.projectdb,
inqueue=g.fetcher2processor, status_queue=g.status_queue,
newtask_queue=g.newtask_queue, result_queue=g.processor2result,
enable_stdout_capture=enable_stdout_capture,
process_time_limit=process_time_limit)
g.instances.append(processor)
if g.get('testing_mode') or get_object:
return processor
processor.run() | python | def processor(ctx, processor_cls, process_time_limit, enable_stdout_capture=True, get_object=False):
"""
Run Processor.
"""
g = ctx.obj
Processor = load_cls(None, None, processor_cls)
processor = Processor(projectdb=g.projectdb,
inqueue=g.fetcher2processor, status_queue=g.status_queue,
newtask_queue=g.newtask_queue, result_queue=g.processor2result,
enable_stdout_capture=enable_stdout_capture,
process_time_limit=process_time_limit)
g.instances.append(processor)
if g.get('testing_mode') or get_object:
return processor
processor.run() | ['def', 'processor', '(', 'ctx', ',', 'processor_cls', ',', 'process_time_limit', ',', 'enable_stdout_capture', '=', 'True', ',', 'get_object', '=', 'False', ')', ':', 'g', '=', 'ctx', '.', 'obj', 'Processor', '=', 'load_cls', '(', 'None', ',', 'None', ',', 'processor_cls', ')', 'processor', '=', 'Processor', '(', 'projectdb', '=', 'g', '.', 'projectdb', ',', 'inqueue', '=', 'g', '.', 'fetcher2processor', ',', 'status_queue', '=', 'g', '.', 'status_queue', ',', 'newtask_queue', '=', 'g', '.', 'newtask_queue', ',', 'result_queue', '=', 'g', '.', 'processor2result', ',', 'enable_stdout_capture', '=', 'enable_stdout_capture', ',', 'process_time_limit', '=', 'process_time_limit', ')', 'g', '.', 'instances', '.', 'append', '(', 'processor', ')', 'if', 'g', '.', 'get', '(', "'testing_mode'", ')', 'or', 'get_object', ':', 'return', 'processor', 'processor', '.', 'run', '(', ')'] | Run Processor. | ['Run', 'Processor', '.'] | train | https://github.com/binux/pyspider/blob/3fccfabe2b057b7a56d4a4c79dc0dd6cd2239fe9/pyspider/run.py#L277-L294 |
6,218 | tumblr/pytumblr | pytumblr/__init__.py | TumblrRestClient.create_photo | def create_photo(self, blogname, **kwargs):
"""
Create a photo post or photoset on a blog
:param blogname: a string, the url of the blog you want to post to.
:param state: a string, The state of the post.
:param tags: a list of tags that you want applied to the post
:param tweet: a string, the customized tweet that you want
:param date: a string, the GMT date and time of the post
:param format: a string, sets the format type of the post. html or markdown
:param slug: a string, a short text summary to the end of the post url
:param caption: a string, the caption that you want applied to the photo
:param link: a string, the 'click-through' url you want on the photo
:param source: a string, the photo source url
:param data: a string or a list of the path of photo(s)
:returns: a dict created from the JSON response
"""
kwargs.update({"type": "photo"})
return self._send_post(blogname, kwargs) | python | def create_photo(self, blogname, **kwargs):
"""
Create a photo post or photoset on a blog
:param blogname: a string, the url of the blog you want to post to.
:param state: a string, The state of the post.
:param tags: a list of tags that you want applied to the post
:param tweet: a string, the customized tweet that you want
:param date: a string, the GMT date and time of the post
:param format: a string, sets the format type of the post. html or markdown
:param slug: a string, a short text summary to the end of the post url
:param caption: a string, the caption that you want applied to the photo
:param link: a string, the 'click-through' url you want on the photo
:param source: a string, the photo source url
:param data: a string or a list of the path of photo(s)
:returns: a dict created from the JSON response
"""
kwargs.update({"type": "photo"})
return self._send_post(blogname, kwargs) | ['def', 'create_photo', '(', 'self', ',', 'blogname', ',', '*', '*', 'kwargs', ')', ':', 'kwargs', '.', 'update', '(', '{', '"type"', ':', '"photo"', '}', ')', 'return', 'self', '.', '_send_post', '(', 'blogname', ',', 'kwargs', ')'] | Create a photo post or photoset on a blog
:param blogname: a string, the url of the blog you want to post to.
:param state: a string, The state of the post.
:param tags: a list of tags that you want applied to the post
:param tweet: a string, the customized tweet that you want
:param date: a string, the GMT date and time of the post
:param format: a string, sets the format type of the post. html or markdown
:param slug: a string, a short text summary to the end of the post url
:param caption: a string, the caption that you want applied to the photo
:param link: a string, the 'click-through' url you want on the photo
:param source: a string, the photo source url
:param data: a string or a list of the path of photo(s)
:returns: a dict created from the JSON response | ['Create', 'a', 'photo', 'post', 'or', 'photoset', 'on', 'a', 'blog'] | train | https://github.com/tumblr/pytumblr/blob/4a5cd7c4b8ae78d12811d9fd52620afa1692a415/pytumblr/__init__.py#L289-L308 |
6,219 | david-cortes/costsensitive | costsensitive/__init__.py | FilterTree.fit | def fit(self, X, C):
"""
Fit a filter tree classifier
Note
----
Shifting the order of the classes within the cost array will produce different
results, as it will build a different binary tree comparing different classes
at each node.
Parameters
----------
X : array (n_samples, n_features)
The data on which to fit a cost-sensitive classifier.
C : array (n_samples, n_classes)
The cost of predicting each label for each observation (more means worse).
"""
X,C = _check_fit_input(X,C)
C = np.asfortranarray(C)
nclasses=C.shape[1]
self.tree=_BinTree(nclasses)
self.classifiers=[deepcopy(self.base_classifier) for c in range(nclasses-1)]
classifier_queue=self.tree.is_at_bottom
next_round=list()
already_fitted=set()
labels_take=-np.ones((X.shape[0],len(self.classifiers)))
while True:
for c in classifier_queue:
if c in already_fitted or (c is None):
continue
child1, child2 = self.tree.childs[c]
if (child1>0) and (child1 not in already_fitted):
continue
if (child2>0) and (child2 not in already_fitted):
continue
if child1<=0:
class1=-np.repeat(child1,X.shape[0]).astype("int64")
else:
class1=labels_take[:, child1].astype("int64")
if child2<=0:
class2=-np.repeat(child2,X.shape[0]).astype("int64")
else:
class2=labels_take[:, child2].astype("int64")
cost1=C[np.arange(X.shape[0]),np.clip(class1,a_min=0,a_max=None)]
cost2=C[np.arange(X.shape[0]),np.clip(class2,a_min=0,a_max=None)]
y=(cost1<cost2).astype('uint8')
w=np.abs(cost1-cost2)
valid_obs=w>0
if child1>0:
valid_obs=valid_obs&(labels_take[:,child1]>=0)
if child2>0:
valid_obs=valid_obs&(labels_take[:,child2]>=0)
X_take=X[valid_obs,:]
y_take=y[valid_obs]
w_take=w[valid_obs]
w_take=_standardize_weights(w_take)
self.classifiers[c].fit(X_take,y_take,sample_weight=w_take)
labels_arr=np.c_[class1,class2].astype("int64")
labels_take[valid_obs,c]=labels_arr[np.repeat(0,X_take.shape[0]),\
self.classifiers[c].predict(X_take).reshape(-1).astype('uint8')]
already_fitted.add(c)
next_round.append(self.tree.parents[c])
if c==0 or (len(classifier_queue)==0):
break
classifier_queue=list(set(next_round))
next_round=list()
if (len(classifier_queue)==0):
break
return self | python | def fit(self, X, C):
"""
Fit a filter tree classifier
Note
----
Shifting the order of the classes within the cost array will produce different
results, as it will build a different binary tree comparing different classes
at each node.
Parameters
----------
X : array (n_samples, n_features)
The data on which to fit a cost-sensitive classifier.
C : array (n_samples, n_classes)
The cost of predicting each label for each observation (more means worse).
"""
X,C = _check_fit_input(X,C)
C = np.asfortranarray(C)
nclasses=C.shape[1]
self.tree=_BinTree(nclasses)
self.classifiers=[deepcopy(self.base_classifier) for c in range(nclasses-1)]
classifier_queue=self.tree.is_at_bottom
next_round=list()
already_fitted=set()
labels_take=-np.ones((X.shape[0],len(self.classifiers)))
while True:
for c in classifier_queue:
if c in already_fitted or (c is None):
continue
child1, child2 = self.tree.childs[c]
if (child1>0) and (child1 not in already_fitted):
continue
if (child2>0) and (child2 not in already_fitted):
continue
if child1<=0:
class1=-np.repeat(child1,X.shape[0]).astype("int64")
else:
class1=labels_take[:, child1].astype("int64")
if child2<=0:
class2=-np.repeat(child2,X.shape[0]).astype("int64")
else:
class2=labels_take[:, child2].astype("int64")
cost1=C[np.arange(X.shape[0]),np.clip(class1,a_min=0,a_max=None)]
cost2=C[np.arange(X.shape[0]),np.clip(class2,a_min=0,a_max=None)]
y=(cost1<cost2).astype('uint8')
w=np.abs(cost1-cost2)
valid_obs=w>0
if child1>0:
valid_obs=valid_obs&(labels_take[:,child1]>=0)
if child2>0:
valid_obs=valid_obs&(labels_take[:,child2]>=0)
X_take=X[valid_obs,:]
y_take=y[valid_obs]
w_take=w[valid_obs]
w_take=_standardize_weights(w_take)
self.classifiers[c].fit(X_take,y_take,sample_weight=w_take)
labels_arr=np.c_[class1,class2].astype("int64")
labels_take[valid_obs,c]=labels_arr[np.repeat(0,X_take.shape[0]),\
self.classifiers[c].predict(X_take).reshape(-1).astype('uint8')]
already_fitted.add(c)
next_round.append(self.tree.parents[c])
if c==0 or (len(classifier_queue)==0):
break
classifier_queue=list(set(next_round))
next_round=list()
if (len(classifier_queue)==0):
break
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Note
----
Shifting the order of the classes within the cost array will produce different
results, as it will build a different binary tree comparing different classes
at each node.
Parameters
----------
X : array (n_samples, n_features)
The data on which to fit a cost-sensitive classifier.
C : array (n_samples, n_classes)
The cost of predicting each label for each observation (more means worse). | ['Fit', 'a', 'filter', 'tree', 'classifier', 'Note', '----', 'Shifting', 'the', 'order', 'of', 'the', 'classes', 'within', 'the', 'cost', 'array', 'will', 'produce', 'different', 'results', 'as', 'it', 'will', 'build', 'a', 'different', 'binary', 'tree', 'comparing', 'different', 'classes', 'at', 'each', 'node', '.', 'Parameters', '----------', 'X', ':', 'array', '(', 'n_samples', 'n_features', ')', 'The', 'data', 'on', 'which', 'to', 'fit', 'a', 'cost', '-', 'sensitive', 'classifier', '.', 'C', ':', 'array', '(', 'n_samples', 'n_classes', ')', 'The', 'cost', 'of', 'predicting', 'each', 'label', 'for', 'each', 'observation', '(', 'more', 'means', 'worse', ')', '.'] | train | https://github.com/david-cortes/costsensitive/blob/355fbf20397ce673ce9e22048b6c52dbeeb354cc/costsensitive/__init__.py#L387-L462 |
6,220 | NICTA/revrand | revrand/mathfun/special.py | softplus | def softplus(X):
""" Pass X through a soft-plus function, , in a numerically
stable way (using the log-sum-exp trick).
The softplus transformation is:
.. math::
\log(1 + \exp\{X\})
Parameters
----------
X: ndarray
shape (N,) array or shape (N, D) array of data.
Returns
-------
spX: ndarray
array of same shape of X with the result of softmax(X).
"""
if np.isscalar(X):
return logsumexp(np.vstack((np.zeros(1), [X])).T, axis=1)[0]
N = X.shape[0]
if X.ndim == 1:
return logsumexp(np.vstack((np.zeros(N), X)).T, axis=1)
elif X.ndim == 2:
sftX = np.empty(X.shape, dtype=float)
for d in range(X.shape[1]):
sftX[:, d] = logsumexp(np.vstack((np.zeros(N), X[:, d])).T, axis=1)
return sftX
else:
raise ValueError("This only works on up to 2D arrays.") | python | def softplus(X):
""" Pass X through a soft-plus function, , in a numerically
stable way (using the log-sum-exp trick).
The softplus transformation is:
.. math::
\log(1 + \exp\{X\})
Parameters
----------
X: ndarray
shape (N,) array or shape (N, D) array of data.
Returns
-------
spX: ndarray
array of same shape of X with the result of softmax(X).
"""
if np.isscalar(X):
return logsumexp(np.vstack((np.zeros(1), [X])).T, axis=1)[0]
N = X.shape[0]
if X.ndim == 1:
return logsumexp(np.vstack((np.zeros(N), X)).T, axis=1)
elif X.ndim == 2:
sftX = np.empty(X.shape, dtype=float)
for d in range(X.shape[1]):
sftX[:, d] = logsumexp(np.vstack((np.zeros(N), X[:, d])).T, axis=1)
return sftX
else:
raise ValueError("This only works on up to 2D arrays.") | ['def', 'softplus', '(', 'X', ')', ':', 'if', 'np', '.', 'isscalar', '(', 'X', ')', ':', 'return', 'logsumexp', '(', 'np', '.', 'vstack', '(', '(', 'np', '.', 'zeros', '(', '1', ')', ',', '[', 'X', ']', ')', ')', '.', 'T', ',', 'axis', '=', '1', ')', '[', '0', ']', 'N', '=', 'X', '.', 'shape', '[', '0', ']', 'if', 'X', '.', 'ndim', '==', '1', ':', 'return', 'logsumexp', '(', 'np', '.', 'vstack', '(', '(', 'np', '.', 'zeros', '(', 'N', ')', ',', 'X', ')', ')', '.', 'T', ',', 'axis', '=', '1', ')', 'elif', 'X', '.', 'ndim', '==', '2', ':', 'sftX', '=', 'np', '.', 'empty', '(', 'X', '.', 'shape', ',', 'dtype', '=', 'float', ')', 'for', 'd', 'in', 'range', '(', 'X', '.', 'shape', '[', '1', ']', ')', ':', 'sftX', '[', ':', ',', 'd', ']', '=', 'logsumexp', '(', 'np', '.', 'vstack', '(', '(', 'np', '.', 'zeros', '(', 'N', ')', ',', 'X', '[', ':', ',', 'd', ']', ')', ')', '.', 'T', ',', 'axis', '=', '1', ')', 'return', 'sftX', 'else', ':', 'raise', 'ValueError', '(', '"This only works on up to 2D arrays."', ')'] | Pass X through a soft-plus function, , in a numerically
stable way (using the log-sum-exp trick).
The softplus transformation is:
.. math::
\log(1 + \exp\{X\})
Parameters
----------
X: ndarray
shape (N,) array or shape (N, D) array of data.
Returns
-------
spX: ndarray
array of same shape of X with the result of softmax(X). | ['Pass', 'X', 'through', 'a', 'soft', '-', 'plus', 'function', 'in', 'a', 'numerically', 'stable', 'way', '(', 'using', 'the', 'log', '-', 'sum', '-', 'exp', 'trick', ')', '.'] | train | https://github.com/NICTA/revrand/blob/4c1881b6c1772d2b988518e49dde954f165acfb6/revrand/mathfun/special.py#L91-L124 |
6,221 | TylerGubala/bpy-build | setup.py | InstallCMakeLibs.run | def run(self):
"""
Copy libraries from the bin directory and place them as appropriate
"""
self.announce("Moving library files", level=3)
# We have already built the libraries in the previous build_ext step
self.skip_build = True
bin_dir = self.distribution.bin_dir
libs = [os.path.join(bin_dir, _lib) for _lib in
os.listdir(bin_dir) if
os.path.isfile(os.path.join(bin_dir, _lib)) and
os.path.splitext(_lib)[1] in [".dll", ".so"]
and not (_lib.startswith("python") or _lib.startswith("bpy"))]
for lib in libs:
shutil.move(lib, os.path.join(self.build_dir,
os.path.basename(lib)))
# Mark the libs for installation, adding them to
# distribution.data_files seems to ensure that setuptools' record
# writer appends them to installed-files.txt in the package's egg-info
#
# Also tried adding the libraries to the distribution.libraries list,
# but that never seemed to add them to the installed-files.txt in the
# egg-info, and the online recommendation seems to be adding libraries
# into eager_resources in the call to setup(), which I think puts them
# in data_files anyways.
#
# What is the best way?
self.distribution.data_files = [os.path.join(self.install_dir,
os.path.basename(lib))
for lib in libs]
# Must be forced to run after adding the libs to data_files
self.distribution.run_command("install_data")
super().run() | python | def run(self):
"""
Copy libraries from the bin directory and place them as appropriate
"""
self.announce("Moving library files", level=3)
# We have already built the libraries in the previous build_ext step
self.skip_build = True
bin_dir = self.distribution.bin_dir
libs = [os.path.join(bin_dir, _lib) for _lib in
os.listdir(bin_dir) if
os.path.isfile(os.path.join(bin_dir, _lib)) and
os.path.splitext(_lib)[1] in [".dll", ".so"]
and not (_lib.startswith("python") or _lib.startswith("bpy"))]
for lib in libs:
shutil.move(lib, os.path.join(self.build_dir,
os.path.basename(lib)))
# Mark the libs for installation, adding them to
# distribution.data_files seems to ensure that setuptools' record
# writer appends them to installed-files.txt in the package's egg-info
#
# Also tried adding the libraries to the distribution.libraries list,
# but that never seemed to add them to the installed-files.txt in the
# egg-info, and the online recommendation seems to be adding libraries
# into eager_resources in the call to setup(), which I think puts them
# in data_files anyways.
#
# What is the best way?
self.distribution.data_files = [os.path.join(self.install_dir,
os.path.basename(lib))
for lib in libs]
# Must be forced to run after adding the libs to data_files
self.distribution.run_command("install_data")
super().run() | ['def', 'run', '(', 'self', ')', ':', 'self', '.', 'announce', '(', '"Moving library files"', ',', 'level', '=', '3', ')', '# We have already built the libraries in the previous build_ext step', 'self', '.', 'skip_build', '=', 'True', 'bin_dir', '=', 'self', '.', 'distribution', '.', 'bin_dir', 'libs', '=', '[', 'os', '.', 'path', '.', 'join', '(', 'bin_dir', ',', '_lib', ')', 'for', '_lib', 'in', 'os', '.', 'listdir', '(', 'bin_dir', ')', 'if', 'os', '.', 'path', '.', 'isfile', '(', 'os', '.', 'path', '.', 'join', '(', 'bin_dir', ',', '_lib', ')', ')', 'and', 'os', '.', 'path', '.', 'splitext', '(', '_lib', ')', '[', '1', ']', 'in', '[', '".dll"', ',', '".so"', ']', 'and', 'not', '(', '_lib', '.', 'startswith', '(', '"python"', ')', 'or', '_lib', '.', 'startswith', '(', '"bpy"', ')', ')', ']', 'for', 'lib', 'in', 'libs', ':', 'shutil', '.', 'move', '(', 'lib', ',', 'os', '.', 'path', '.', 'join', '(', 'self', '.', 'build_dir', ',', 'os', '.', 'path', '.', 'basename', '(', 'lib', ')', ')', ')', '# Mark the libs for installation, adding them to ', "# distribution.data_files seems to ensure that setuptools' record ", "# writer appends them to installed-files.txt in the package's egg-info", '#', '# Also tried adding the libraries to the distribution.libraries list, ', '# but that never seemed to add them to the installed-files.txt in the ', '# egg-info, and the online recommendation seems to be adding libraries ', '# into eager_resources in the call to setup(), which I think puts them ', '# in data_files anyways. ', '# ', '# What is the best way?', 'self', '.', 'distribution', '.', 'data_files', '=', '[', 'os', '.', 'path', '.', 'join', '(', 'self', '.', 'install_dir', ',', 'os', '.', 'path', '.', 'basename', '(', 'lib', ')', ')', 'for', 'lib', 'in', 'libs', ']', '# Must be forced to run after adding the libs to data_files', 'self', '.', 'distribution', '.', 'run_command', '(', '"install_data"', ')', 'super', '(', ')', '.', 'run', '(', ')'] | Copy libraries from the bin directory and place them as appropriate | ['Copy', 'libraries', 'from', 'the', 'bin', 'directory', 'and', 'place', 'them', 'as', 'appropriate'] | train | https://github.com/TylerGubala/bpy-build/blob/667d41526a346cfa271e26c5d675689c7ab1a254/setup.py#L181-L225 |
6,222 | MycroftAI/adapt | adapt/intent.py | find_first_tag | def find_first_tag(tags, entity_type, after_index=-1):
"""Searches tags for entity type after given index
Args:
tags(list): a list of tags with entity types to be compaired too entity_type
entity_type(str): This is he entity type to be looking for in tags
after_index(int): the start token must be greaterthan this.
Returns:
( tag, v, confidence ):
tag(str): is the tag that matched
v(str): ? the word that matched?
confidence(float): is a mesure of accuacy. 1 is full confidence and 0 is none.
"""
for tag in tags:
for entity in tag.get('entities'):
for v, t in entity.get('data'):
if t.lower() == entity_type.lower() and tag.get('start_token', 0) > after_index:
return tag, v, entity.get('confidence')
return None, None, None | python | def find_first_tag(tags, entity_type, after_index=-1):
"""Searches tags for entity type after given index
Args:
tags(list): a list of tags with entity types to be compaired too entity_type
entity_type(str): This is he entity type to be looking for in tags
after_index(int): the start token must be greaterthan this.
Returns:
( tag, v, confidence ):
tag(str): is the tag that matched
v(str): ? the word that matched?
confidence(float): is a mesure of accuacy. 1 is full confidence and 0 is none.
"""
for tag in tags:
for entity in tag.get('entities'):
for v, t in entity.get('data'):
if t.lower() == entity_type.lower() and tag.get('start_token', 0) > after_index:
return tag, v, entity.get('confidence')
return None, None, None | ['def', 'find_first_tag', '(', 'tags', ',', 'entity_type', ',', 'after_index', '=', '-', '1', ')', ':', 'for', 'tag', 'in', 'tags', ':', 'for', 'entity', 'in', 'tag', '.', 'get', '(', "'entities'", ')', ':', 'for', 'v', ',', 't', 'in', 'entity', '.', 'get', '(', "'data'", ')', ':', 'if', 't', '.', 'lower', '(', ')', '==', 'entity_type', '.', 'lower', '(', ')', 'and', 'tag', '.', 'get', '(', "'start_token'", ',', '0', ')', '>', 'after_index', ':', 'return', 'tag', ',', 'v', ',', 'entity', '.', 'get', '(', "'confidence'", ')', 'return', 'None', ',', 'None', ',', 'None'] | Searches tags for entity type after given index
Args:
tags(list): a list of tags with entity types to be compaired too entity_type
entity_type(str): This is he entity type to be looking for in tags
after_index(int): the start token must be greaterthan this.
Returns:
( tag, v, confidence ):
tag(str): is the tag that matched
v(str): ? the word that matched?
confidence(float): is a mesure of accuacy. 1 is full confidence and 0 is none. | ['Searches', 'tags', 'for', 'entity', 'type', 'after', 'given', 'index'] | train | https://github.com/MycroftAI/adapt/blob/334f23248b8e09fb9d84a88398424ec5bd3bae4c/adapt/intent.py#L29-L49 |
6,223 | saltstack/salt | salt/modules/keystone.py | service_create | def service_create(name, service_type, description=None, profile=None,
**connection_args):
'''
Add service to Keystone service catalog
CLI Examples:
.. code-block:: bash
salt '*' keystone.service_create nova compute \
'OpenStack Compute Service'
'''
kstone = auth(profile, **connection_args)
service = kstone.services.create(name, service_type, description=description)
return service_get(service.id, profile=profile, **connection_args) | python | def service_create(name, service_type, description=None, profile=None,
**connection_args):
'''
Add service to Keystone service catalog
CLI Examples:
.. code-block:: bash
salt '*' keystone.service_create nova compute \
'OpenStack Compute Service'
'''
kstone = auth(profile, **connection_args)
service = kstone.services.create(name, service_type, description=description)
return service_get(service.id, profile=profile, **connection_args) | ['def', 'service_create', '(', 'name', ',', 'service_type', ',', 'description', '=', 'None', ',', 'profile', '=', 'None', ',', '*', '*', 'connection_args', ')', ':', 'kstone', '=', 'auth', '(', 'profile', ',', '*', '*', 'connection_args', ')', 'service', '=', 'kstone', '.', 'services', '.', 'create', '(', 'name', ',', 'service_type', ',', 'description', '=', 'description', ')', 'return', 'service_get', '(', 'service', '.', 'id', ',', 'profile', '=', 'profile', ',', '*', '*', 'connection_args', ')'] | Add service to Keystone service catalog
CLI Examples:
.. code-block:: bash
salt '*' keystone.service_create nova compute \
'OpenStack Compute Service' | ['Add', 'service', 'to', 'Keystone', 'service', 'catalog'] | train | https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/modules/keystone.py#L525-L539 |
6,224 | apache/incubator-mxnet | example/rnn/large_word_lm/model.py | generate_samples | def generate_samples(label, num_splits, sampler):
""" Split labels into `num_splits` and
generate candidates based on log-uniform distribution.
"""
def listify(x):
return x if isinstance(x, list) else [x]
label_splits = listify(label.split(num_splits, axis=0))
prob_samples = []
prob_targets = []
samples = []
for label_split in label_splits:
label_split_2d = label_split.reshape((-1,1))
sampled_value = sampler.draw(label_split_2d)
sampled_classes, exp_cnt_true, exp_cnt_sampled = sampled_value
samples.append(sampled_classes.astype(np.float32))
prob_targets.append(exp_cnt_true.astype(np.float32).reshape((-1,1)))
prob_samples.append(exp_cnt_sampled.astype(np.float32))
return samples, prob_samples, prob_targets | python | def generate_samples(label, num_splits, sampler):
""" Split labels into `num_splits` and
generate candidates based on log-uniform distribution.
"""
def listify(x):
return x if isinstance(x, list) else [x]
label_splits = listify(label.split(num_splits, axis=0))
prob_samples = []
prob_targets = []
samples = []
for label_split in label_splits:
label_split_2d = label_split.reshape((-1,1))
sampled_value = sampler.draw(label_split_2d)
sampled_classes, exp_cnt_true, exp_cnt_sampled = sampled_value
samples.append(sampled_classes.astype(np.float32))
prob_targets.append(exp_cnt_true.astype(np.float32).reshape((-1,1)))
prob_samples.append(exp_cnt_sampled.astype(np.float32))
return samples, prob_samples, prob_targets | ['def', 'generate_samples', '(', 'label', ',', 'num_splits', ',', 'sampler', ')', ':', 'def', 'listify', '(', 'x', ')', ':', 'return', 'x', 'if', 'isinstance', '(', 'x', ',', 'list', ')', 'else', '[', 'x', ']', 'label_splits', '=', 'listify', '(', 'label', '.', 'split', '(', 'num_splits', ',', 'axis', '=', '0', ')', ')', 'prob_samples', '=', '[', ']', 'prob_targets', '=', '[', ']', 'samples', '=', '[', ']', 'for', 'label_split', 'in', 'label_splits', ':', 'label_split_2d', '=', 'label_split', '.', 'reshape', '(', '(', '-', '1', ',', '1', ')', ')', 'sampled_value', '=', 'sampler', '.', 'draw', '(', 'label_split_2d', ')', 'sampled_classes', ',', 'exp_cnt_true', ',', 'exp_cnt_sampled', '=', 'sampled_value', 'samples', '.', 'append', '(', 'sampled_classes', '.', 'astype', '(', 'np', '.', 'float32', ')', ')', 'prob_targets', '.', 'append', '(', 'exp_cnt_true', '.', 'astype', '(', 'np', '.', 'float32', ')', '.', 'reshape', '(', '(', '-', '1', ',', '1', ')', ')', ')', 'prob_samples', '.', 'append', '(', 'exp_cnt_sampled', '.', 'astype', '(', 'np', '.', 'float32', ')', ')', 'return', 'samples', ',', 'prob_samples', ',', 'prob_targets'] | Split labels into `num_splits` and
generate candidates based on log-uniform distribution. | ['Split', 'labels', 'into', 'num_splits', 'and', 'generate', 'candidates', 'based', 'on', 'log', '-', 'uniform', 'distribution', '.'] | train | https://github.com/apache/incubator-mxnet/blob/1af29e9c060a4c7d60eeaacba32afdb9a7775ba7/example/rnn/large_word_lm/model.py#L130-L147 |
6,225 | rjdkmr/do_x3dna | dnaMD/dnaMD/dnaEY.py | dnaEY.getGlobalDeformationEnergy | def getGlobalDeformationEnergy(self, bp, complexDna, freeDnaFrames=None, boundDnaFrames=None, paxis='Z',
which='all', masked=False, outFile=None):
r"""Deformation energy of the input DNA using Global elastic properties
It can be used to calculated deformation energy of a input DNA with reference to the DNA present in the current
object.
The deformation free energy is calculated using elastic matrix as follows
.. math::
G = \frac{1}{2L_0}\mathbf{xKx^T}
.. math::
\mathbf{x} = \begin{bmatrix}
(\theta^{x} - \theta^{x}_0) & (\theta^{y} - \theta^{y}_0) & (L - L_0) & (\phi - \phi_0)
\end{bmatrix}
.. currentmodule:: dnaMD
Parameters
----------
bp : list
List of two base-steps forming the DNA segment.
For example: with ``bp=[5, 50]``, 5-50 base-step segment will be considered.
complexDna : :class:`dnaMD.DNA`
Input :class:`dnaMD.DNA` instance for which deformation energy will be calculated.
freeDnaFrames : list
To select a trajectory segment of current (free) DNA data.
List of two trajectory frames between which parameters will be extracted. It can be used to select portions
of the trajectory. For example, with ``frames=[100, 1000]``, 100th to 1000th frame of the trajectory will be
considered.
boundDnaFrames : list
To select a trajectory segment of input (bound) DNA data.
List of two trajectory frames between which parameters will be extracted. It can be used to select portions
of the trajectory. For example, with ``frames=[100, 1000]``, 100th to 1000th frame of the trajectory will be
considered.
paxis : str
Axis parallel to global helical-axis(``'X'``, or ``'Y'`` or ``'Z'``). Only require when bending motions are
included in the calculation.
which : str or list
For which motions, energy should be calculated. It should be either a list containing terms listed below or
"all" for all energy terms.
Following keywords are available:
* ``'full'`` : Use entire elastic matrix -- all motions with their coupling
* ``'diag'`` : Use diagonal of elastic matrix -- all motions but no coupling
* ``'b1'`` : Only bending-1 motion
* ``'b2'`` : Only bending-2 motion
* ``'stretch'`` : Only stretching motion
* ``'twist'`` : Only Twisting motions
* ``'st_coupling'`` : Only stretch-twist coupling motion
* ``'bs_coupling'`` : Only Bending and stretching coupling
* ``'bt_coupling'`` : Only Bending and Twisting coupling
* ``'bb_coupling'`` : Only bending-1 and bending-2 coupling
* ``'bend'`` : Both bending motions with their coupling
* ``'st'`` : Stretching and twisting motions with their coupling
* ``'bs'`` : Bending (b1, b2) and stretching motions with their coupling
* ``'bt'`` : Bending (b1, b2) and twisting motions with their coupling
masked : bool
``Default=False``. To skip specific frames/snapshots.
``DNA.mask`` array should be set to use this functionality.
This array contains boolean (either ``True`` or ``False``) value
for each frame to mask the frames. Presently, mask array is
automatically generated during :meth:`dnaMD.DNA.generate_smooth_axis` to
skip those frames where 3D fitting curve was not successful within
the given criteria.
outFile : str
Output file in csv format.
Returns
-------
time : numpy.ndarray
1D array containing time values.
energy : OrderedDict of numpy.ndarray
Dictionary of 1D array of shape (nframes) containing energy terms requested for DNA.
"""
if self.esType == 'BST':
energyTerms = self.enGlobalTypes
else:
energyTerms = self.enGlobalTypes[:5]
if isinstance(which, str):
if which != 'all':
raise ValueError('Either use "all" or use list of terms from this {0} list \n.'.format(energyTerms))
else:
which = energyTerms
elif isinstance(which, list):
for key in which:
if key not in energyTerms:
raise ValueError('{0} is not a supported keyword.\n Use from the following list: \n{1}'.format(
which, energyTerms))
else:
raise ValueError('Either use "all" or use list of terms from this {0} list \n.'.format(
energyTerms))
if self.esType == 'BST':
means, esMatrix = self.getStretchTwistBendModulus(bp, frames=freeDnaFrames, masked=masked,
matrix=True, paxis=paxis)
else:
means, esMatrix = self.getStretchTwistModulus(bp, frames=freeDnaFrames, masked=masked, matrix=True)
esMatrix = 2.5 * esMatrix # Convert kT to kJ/mol
time, array = self.extractGlobalParameters(complexDna, bp, frames=boundDnaFrames, paxis=paxis, masked=masked)
# Initialize energy dictionary
energyOut = OrderedDict()
for key in which:
energyOut[key] = []
for i in range(array[0].shape[0]):
vec = array[:, i]
diff = vec - means
for key in which:
if self.esType == 'BST':
t_energy = self._calcEnergyBendStretchTwist(diff, esMatrix, key)
else:
t_energy = self._calcEnergyStretchTwist(diff, esMatrix, key)
energyOut[key].append(t_energy)
for key in which:
energyOut[key] = np.asarray(energyOut[key])
# Write output file
if outFile is not None:
with open(outFile, 'w') as fout:
fout.write('#Time')
for name in which:
fout.write(', {0}'.format(name))
fout.write('\n')
for t in range(len(time)):
fout.write('{0:.3f}'.format(time[t]))
for name in which:
fout.write(', {0:.5f}'.format(energyOut[name][t]))
fout.write('\n')
return time, energyOut | python | def getGlobalDeformationEnergy(self, bp, complexDna, freeDnaFrames=None, boundDnaFrames=None, paxis='Z',
which='all', masked=False, outFile=None):
r"""Deformation energy of the input DNA using Global elastic properties
It can be used to calculated deformation energy of a input DNA with reference to the DNA present in the current
object.
The deformation free energy is calculated using elastic matrix as follows
.. math::
G = \frac{1}{2L_0}\mathbf{xKx^T}
.. math::
\mathbf{x} = \begin{bmatrix}
(\theta^{x} - \theta^{x}_0) & (\theta^{y} - \theta^{y}_0) & (L - L_0) & (\phi - \phi_0)
\end{bmatrix}
.. currentmodule:: dnaMD
Parameters
----------
bp : list
List of two base-steps forming the DNA segment.
For example: with ``bp=[5, 50]``, 5-50 base-step segment will be considered.
complexDna : :class:`dnaMD.DNA`
Input :class:`dnaMD.DNA` instance for which deformation energy will be calculated.
freeDnaFrames : list
To select a trajectory segment of current (free) DNA data.
List of two trajectory frames between which parameters will be extracted. It can be used to select portions
of the trajectory. For example, with ``frames=[100, 1000]``, 100th to 1000th frame of the trajectory will be
considered.
boundDnaFrames : list
To select a trajectory segment of input (bound) DNA data.
List of two trajectory frames between which parameters will be extracted. It can be used to select portions
of the trajectory. For example, with ``frames=[100, 1000]``, 100th to 1000th frame of the trajectory will be
considered.
paxis : str
Axis parallel to global helical-axis(``'X'``, or ``'Y'`` or ``'Z'``). Only require when bending motions are
included in the calculation.
which : str or list
For which motions, energy should be calculated. It should be either a list containing terms listed below or
"all" for all energy terms.
Following keywords are available:
* ``'full'`` : Use entire elastic matrix -- all motions with their coupling
* ``'diag'`` : Use diagonal of elastic matrix -- all motions but no coupling
* ``'b1'`` : Only bending-1 motion
* ``'b2'`` : Only bending-2 motion
* ``'stretch'`` : Only stretching motion
* ``'twist'`` : Only Twisting motions
* ``'st_coupling'`` : Only stretch-twist coupling motion
* ``'bs_coupling'`` : Only Bending and stretching coupling
* ``'bt_coupling'`` : Only Bending and Twisting coupling
* ``'bb_coupling'`` : Only bending-1 and bending-2 coupling
* ``'bend'`` : Both bending motions with their coupling
* ``'st'`` : Stretching and twisting motions with their coupling
* ``'bs'`` : Bending (b1, b2) and stretching motions with their coupling
* ``'bt'`` : Bending (b1, b2) and twisting motions with their coupling
masked : bool
``Default=False``. To skip specific frames/snapshots.
``DNA.mask`` array should be set to use this functionality.
This array contains boolean (either ``True`` or ``False``) value
for each frame to mask the frames. Presently, mask array is
automatically generated during :meth:`dnaMD.DNA.generate_smooth_axis` to
skip those frames where 3D fitting curve was not successful within
the given criteria.
outFile : str
Output file in csv format.
Returns
-------
time : numpy.ndarray
1D array containing time values.
energy : OrderedDict of numpy.ndarray
Dictionary of 1D array of shape (nframes) containing energy terms requested for DNA.
"""
if self.esType == 'BST':
energyTerms = self.enGlobalTypes
else:
energyTerms = self.enGlobalTypes[:5]
if isinstance(which, str):
if which != 'all':
raise ValueError('Either use "all" or use list of terms from this {0} list \n.'.format(energyTerms))
else:
which = energyTerms
elif isinstance(which, list):
for key in which:
if key not in energyTerms:
raise ValueError('{0} is not a supported keyword.\n Use from the following list: \n{1}'.format(
which, energyTerms))
else:
raise ValueError('Either use "all" or use list of terms from this {0} list \n.'.format(
energyTerms))
if self.esType == 'BST':
means, esMatrix = self.getStretchTwistBendModulus(bp, frames=freeDnaFrames, masked=masked,
matrix=True, paxis=paxis)
else:
means, esMatrix = self.getStretchTwistModulus(bp, frames=freeDnaFrames, masked=masked, matrix=True)
esMatrix = 2.5 * esMatrix # Convert kT to kJ/mol
time, array = self.extractGlobalParameters(complexDna, bp, frames=boundDnaFrames, paxis=paxis, masked=masked)
# Initialize energy dictionary
energyOut = OrderedDict()
for key in which:
energyOut[key] = []
for i in range(array[0].shape[0]):
vec = array[:, i]
diff = vec - means
for key in which:
if self.esType == 'BST':
t_energy = self._calcEnergyBendStretchTwist(diff, esMatrix, key)
else:
t_energy = self._calcEnergyStretchTwist(diff, esMatrix, key)
energyOut[key].append(t_energy)
for key in which:
energyOut[key] = np.asarray(energyOut[key])
# Write output file
if outFile is not None:
with open(outFile, 'w') as fout:
fout.write('#Time')
for name in which:
fout.write(', {0}'.format(name))
fout.write('\n')
for t in range(len(time)):
fout.write('{0:.3f}'.format(time[t]))
for name in which:
fout.write(', {0:.5f}'.format(energyOut[name][t]))
fout.write('\n')
return time, energyOut | ['def', 'getGlobalDeformationEnergy', '(', 'self', ',', 'bp', ',', 'complexDna', ',', 'freeDnaFrames', '=', 'None', ',', 'boundDnaFrames', '=', 'None', ',', 'paxis', '=', "'Z'", ',', 'which', '=', "'all'", ',', 'masked', '=', 'False', ',', 'outFile', '=', 'None', ')', ':', 'if', 'self', '.', 'esType', '==', "'BST'", ':', 'energyTerms', '=', 'self', '.', 'enGlobalTypes', 'else', ':', 'energyTerms', '=', 'self', '.', 'enGlobalTypes', '[', ':', '5', ']', 'if', 'isinstance', '(', 'which', ',', 'str', ')', ':', 'if', 'which', '!=', "'all'", ':', 'raise', 'ValueError', '(', '\'Either use "all" or use list of terms from this {0} list \\n.\'', '.', 'format', '(', 'energyTerms', ')', ')', 'else', ':', 'which', '=', 'energyTerms', 'elif', 'isinstance', '(', 'which', ',', 'list', ')', ':', 'for', 'key', 'in', 'which', ':', 'if', 'key', 'not', 'in', 'energyTerms', ':', 'raise', 'ValueError', '(', "'{0} is not a supported keyword.\\n Use from the following list: \\n{1}'", '.', 'format', '(', 'which', ',', 'energyTerms', ')', ')', 'else', ':', 'raise', 'ValueError', '(', '\'Either use "all" or use list of terms from this {0} list \\n.\'', '.', 'format', '(', 'energyTerms', ')', ')', 'if', 'self', '.', 'esType', '==', "'BST'", ':', 'means', ',', 'esMatrix', '=', 'self', '.', 'getStretchTwistBendModulus', '(', 'bp', ',', 'frames', '=', 'freeDnaFrames', ',', 'masked', '=', 'masked', ',', 'matrix', '=', 'True', ',', 'paxis', '=', 'paxis', ')', 'else', ':', 'means', ',', 'esMatrix', '=', 'self', '.', 'getStretchTwistModulus', '(', 'bp', ',', 'frames', '=', 'freeDnaFrames', ',', 'masked', '=', 'masked', ',', 'matrix', '=', 'True', ')', 'esMatrix', '=', '2.5', '*', 'esMatrix', '# Convert kT to kJ/mol', 'time', ',', 'array', '=', 'self', '.', 'extractGlobalParameters', '(', 'complexDna', ',', 'bp', ',', 'frames', '=', 'boundDnaFrames', ',', 'paxis', '=', 'paxis', ',', 'masked', '=', 'masked', ')', '# Initialize energy dictionary', 'energyOut', '=', 'OrderedDict', '(', ')', 'for', 'key', 'in', 'which', ':', 'energyOut', '[', 'key', ']', '=', '[', ']', 'for', 'i', 'in', 'range', '(', 'array', '[', '0', ']', '.', 'shape', '[', '0', ']', ')', ':', 'vec', '=', 'array', '[', ':', ',', 'i', ']', 'diff', '=', 'vec', '-', 'means', 'for', 'key', 'in', 'which', ':', 'if', 'self', '.', 'esType', '==', "'BST'", ':', 't_energy', '=', 'self', '.', '_calcEnergyBendStretchTwist', '(', 'diff', ',', 'esMatrix', ',', 'key', ')', 'else', ':', 't_energy', '=', 'self', '.', '_calcEnergyStretchTwist', '(', 'diff', ',', 'esMatrix', ',', 'key', ')', 'energyOut', '[', 'key', ']', '.', 'append', '(', 't_energy', ')', 'for', 'key', 'in', 'which', ':', 'energyOut', '[', 'key', ']', '=', 'np', '.', 'asarray', '(', 'energyOut', '[', 'key', ']', ')', '# Write output file', 'if', 'outFile', 'is', 'not', 'None', ':', 'with', 'open', '(', 'outFile', ',', "'w'", ')', 'as', 'fout', ':', 'fout', '.', 'write', '(', "'#Time'", ')', 'for', 'name', 'in', 'which', ':', 'fout', '.', 'write', '(', "', {0}'", '.', 'format', '(', 'name', ')', ')', 'fout', '.', 'write', '(', "'\\n'", ')', 'for', 't', 'in', 'range', '(', 'len', '(', 'time', ')', ')', ':', 'fout', '.', 'write', '(', "'{0:.3f}'", '.', 'format', '(', 'time', '[', 't', ']', ')', ')', 'for', 'name', 'in', 'which', ':', 'fout', '.', 'write', '(', "', {0:.5f}'", '.', 'format', '(', 'energyOut', '[', 'name', ']', '[', 't', ']', ')', ')', 'fout', '.', 'write', '(', "'\\n'", ')', 'return', 'time', ',', 'energyOut'] | r"""Deformation energy of the input DNA using Global elastic properties
It can be used to calculated deformation energy of a input DNA with reference to the DNA present in the current
object.
The deformation free energy is calculated using elastic matrix as follows
.. math::
G = \frac{1}{2L_0}\mathbf{xKx^T}
.. math::
\mathbf{x} = \begin{bmatrix}
(\theta^{x} - \theta^{x}_0) & (\theta^{y} - \theta^{y}_0) & (L - L_0) & (\phi - \phi_0)
\end{bmatrix}
.. currentmodule:: dnaMD
Parameters
----------
bp : list
List of two base-steps forming the DNA segment.
For example: with ``bp=[5, 50]``, 5-50 base-step segment will be considered.
complexDna : :class:`dnaMD.DNA`
Input :class:`dnaMD.DNA` instance for which deformation energy will be calculated.
freeDnaFrames : list
To select a trajectory segment of current (free) DNA data.
List of two trajectory frames between which parameters will be extracted. It can be used to select portions
of the trajectory. For example, with ``frames=[100, 1000]``, 100th to 1000th frame of the trajectory will be
considered.
boundDnaFrames : list
To select a trajectory segment of input (bound) DNA data.
List of two trajectory frames between which parameters will be extracted. It can be used to select portions
of the trajectory. For example, with ``frames=[100, 1000]``, 100th to 1000th frame of the trajectory will be
considered.
paxis : str
Axis parallel to global helical-axis(``'X'``, or ``'Y'`` or ``'Z'``). Only require when bending motions are
included in the calculation.
which : str or list
For which motions, energy should be calculated. It should be either a list containing terms listed below or
"all" for all energy terms.
Following keywords are available:
* ``'full'`` : Use entire elastic matrix -- all motions with their coupling
* ``'diag'`` : Use diagonal of elastic matrix -- all motions but no coupling
* ``'b1'`` : Only bending-1 motion
* ``'b2'`` : Only bending-2 motion
* ``'stretch'`` : Only stretching motion
* ``'twist'`` : Only Twisting motions
* ``'st_coupling'`` : Only stretch-twist coupling motion
* ``'bs_coupling'`` : Only Bending and stretching coupling
* ``'bt_coupling'`` : Only Bending and Twisting coupling
* ``'bb_coupling'`` : Only bending-1 and bending-2 coupling
* ``'bend'`` : Both bending motions with their coupling
* ``'st'`` : Stretching and twisting motions with their coupling
* ``'bs'`` : Bending (b1, b2) and stretching motions with their coupling
* ``'bt'`` : Bending (b1, b2) and twisting motions with their coupling
masked : bool
``Default=False``. To skip specific frames/snapshots.
``DNA.mask`` array should be set to use this functionality.
This array contains boolean (either ``True`` or ``False``) value
for each frame to mask the frames. Presently, mask array is
automatically generated during :meth:`dnaMD.DNA.generate_smooth_axis` to
skip those frames where 3D fitting curve was not successful within
the given criteria.
outFile : str
Output file in csv format.
Returns
-------
time : numpy.ndarray
1D array containing time values.
energy : OrderedDict of numpy.ndarray
Dictionary of 1D array of shape (nframes) containing energy terms requested for DNA. | ['r', 'Deformation', 'energy', 'of', 'the', 'input', 'DNA', 'using', 'Global', 'elastic', 'properties'] | train | https://github.com/rjdkmr/do_x3dna/blob/fe910335eefcada76737f9e7cd6f25036cd32ab6/dnaMD/dnaMD/dnaEY.py#L653-L795 |
6,226 | CiscoTestAutomation/yang | connector/src/yang/connector/__init__.py | Netconf.request | def request(self, msg, timeout=30):
'''request
High-level api: sends message through NetConf session and returns with
a reply. Exception is thrown out either the reply is in wrong
format or timout. Users can modify timeout value (in seconds) by
passing parameter timeout. Users may want to set a larger timeout when
making a large query.
Parameters
----------
msg : `str`
Any message need to be sent out in XML format. The message can be
in wrong format if it is a negative test case. Because ncclient
tracks same message-id in both rpc and rpc-reply, missing
message-id in your rpc may cause exception when receiving
rpc-reply. Most other wrong format rpc's can be sent without
exception.
timeout : `int`, optional
An optional keyed argument to set timeout value in seconds. Its
default value is 30 seconds.
Returns
-------
str
The reply from the device in string. If something goes wrong, an
exception will be raised.
Raises
------
Exception
If NetConf is not connected, or there is a timeout when receiving
reply.
Code Example::
>>> from pyats.topology import loader
>>> testbed = loader.load('/users/xxx/xxx/asr_20_22.yaml')
>>> device = testbed.devices['asr22']
>>> device.connect(alias='nc', via='netconf')
>>> netconf_request = """
... <rpc message-id="101"
... xmlns="urn:ietf:params:xml:ns:netconf:base:1.0">
... <get>
... <filter>
... <native xmlns="http://cisco.com/ns/yang/ned/ios">
... <version>
... </version>
... </native>
... </filter>
... </get>
... </rpc>
... """
>>> reply = device.nc.request(netconf_request)
>>>
Expected Results::
>>> print(reply)
<?xml version="1.0" encoding="UTF-8"?>
<rpc-reply xmlns="urn:ietf:params:xml:ns:netconf:base:1.0"
message-id="101"><data>
<native xmlns="http://cisco.com/ns/yang/ned/ios">
<version>16.3</version></native></data></rpc-reply>
>>>
'''
rpc = RawRPC(session = self.session,
device_handler = self._device_handler,
timeout = timeout,
raise_mode = operations.rpc.RaiseMode.NONE)
# identify message-id
m = re.search(r'message-id="([A-Za-z0-9_\-:# ]*)"', msg)
if m:
rpc._id = m.group(1)
rpc._listener.register(rpc._id, rpc)
logger.debug('Found message-id="%s" in your rpc, which is good.', rpc._id)
else:
logger.warning('Cannot find message-id in your rpc. You may '
'expect an exception when receiving rpc-reply '
'due to missing message-id.')
return rpc._request(msg).xml | python | def request(self, msg, timeout=30):
'''request
High-level api: sends message through NetConf session and returns with
a reply. Exception is thrown out either the reply is in wrong
format or timout. Users can modify timeout value (in seconds) by
passing parameter timeout. Users may want to set a larger timeout when
making a large query.
Parameters
----------
msg : `str`
Any message need to be sent out in XML format. The message can be
in wrong format if it is a negative test case. Because ncclient
tracks same message-id in both rpc and rpc-reply, missing
message-id in your rpc may cause exception when receiving
rpc-reply. Most other wrong format rpc's can be sent without
exception.
timeout : `int`, optional
An optional keyed argument to set timeout value in seconds. Its
default value is 30 seconds.
Returns
-------
str
The reply from the device in string. If something goes wrong, an
exception will be raised.
Raises
------
Exception
If NetConf is not connected, or there is a timeout when receiving
reply.
Code Example::
>>> from pyats.topology import loader
>>> testbed = loader.load('/users/xxx/xxx/asr_20_22.yaml')
>>> device = testbed.devices['asr22']
>>> device.connect(alias='nc', via='netconf')
>>> netconf_request = """
... <rpc message-id="101"
... xmlns="urn:ietf:params:xml:ns:netconf:base:1.0">
... <get>
... <filter>
... <native xmlns="http://cisco.com/ns/yang/ned/ios">
... <version>
... </version>
... </native>
... </filter>
... </get>
... </rpc>
... """
>>> reply = device.nc.request(netconf_request)
>>>
Expected Results::
>>> print(reply)
<?xml version="1.0" encoding="UTF-8"?>
<rpc-reply xmlns="urn:ietf:params:xml:ns:netconf:base:1.0"
message-id="101"><data>
<native xmlns="http://cisco.com/ns/yang/ned/ios">
<version>16.3</version></native></data></rpc-reply>
>>>
'''
rpc = RawRPC(session = self.session,
device_handler = self._device_handler,
timeout = timeout,
raise_mode = operations.rpc.RaiseMode.NONE)
# identify message-id
m = re.search(r'message-id="([A-Za-z0-9_\-:# ]*)"', msg)
if m:
rpc._id = m.group(1)
rpc._listener.register(rpc._id, rpc)
logger.debug('Found message-id="%s" in your rpc, which is good.', rpc._id)
else:
logger.warning('Cannot find message-id in your rpc. You may '
'expect an exception when receiving rpc-reply '
'due to missing message-id.')
return rpc._request(msg).xml | ['def', 'request', '(', 'self', ',', 'msg', ',', 'timeout', '=', '30', ')', ':', 'rpc', '=', 'RawRPC', '(', 'session', '=', 'self', '.', 'session', ',', 'device_handler', '=', 'self', '.', '_device_handler', ',', 'timeout', '=', 'timeout', ',', 'raise_mode', '=', 'operations', '.', 'rpc', '.', 'RaiseMode', '.', 'NONE', ')', '# identify message-id', 'm', '=', 're', '.', 'search', '(', 'r\'message-id="([A-Za-z0-9_\\-:# ]*)"\'', ',', 'msg', ')', 'if', 'm', ':', 'rpc', '.', '_id', '=', 'm', '.', 'group', '(', '1', ')', 'rpc', '.', '_listener', '.', 'register', '(', 'rpc', '.', '_id', ',', 'rpc', ')', 'logger', '.', 'debug', '(', '\'Found message-id="%s" in your rpc, which is good.\'', ',', 'rpc', '.', '_id', ')', 'else', ':', 'logger', '.', 'warning', '(', "'Cannot find message-id in your rpc. You may '", "'expect an exception when receiving rpc-reply '", "'due to missing message-id.'", ')', 'return', 'rpc', '.', '_request', '(', 'msg', ')', '.', 'xml'] | request
High-level api: sends message through NetConf session and returns with
a reply. Exception is thrown out either the reply is in wrong
format or timout. Users can modify timeout value (in seconds) by
passing parameter timeout. Users may want to set a larger timeout when
making a large query.
Parameters
----------
msg : `str`
Any message need to be sent out in XML format. The message can be
in wrong format if it is a negative test case. Because ncclient
tracks same message-id in both rpc and rpc-reply, missing
message-id in your rpc may cause exception when receiving
rpc-reply. Most other wrong format rpc's can be sent without
exception.
timeout : `int`, optional
An optional keyed argument to set timeout value in seconds. Its
default value is 30 seconds.
Returns
-------
str
The reply from the device in string. If something goes wrong, an
exception will be raised.
Raises
------
Exception
If NetConf is not connected, or there is a timeout when receiving
reply.
Code Example::
>>> from pyats.topology import loader
>>> testbed = loader.load('/users/xxx/xxx/asr_20_22.yaml')
>>> device = testbed.devices['asr22']
>>> device.connect(alias='nc', via='netconf')
>>> netconf_request = """
... <rpc message-id="101"
... xmlns="urn:ietf:params:xml:ns:netconf:base:1.0">
... <get>
... <filter>
... <native xmlns="http://cisco.com/ns/yang/ned/ios">
... <version>
... </version>
... </native>
... </filter>
... </get>
... </rpc>
... """
>>> reply = device.nc.request(netconf_request)
>>>
Expected Results::
>>> print(reply)
<?xml version="1.0" encoding="UTF-8"?>
<rpc-reply xmlns="urn:ietf:params:xml:ns:netconf:base:1.0"
message-id="101"><data>
<native xmlns="http://cisco.com/ns/yang/ned/ios">
<version>16.3</version></native></data></rpc-reply>
>>> | ['request'] | train | https://github.com/CiscoTestAutomation/yang/blob/c70ec5ac5a91f276c4060009203770ece92e76b4/connector/src/yang/connector/__init__.py#L397-L485 |
6,227 | UDST/urbansim | urbansim/models/util.py | columns_in_formula | def columns_in_formula(formula):
"""
Returns the names of all the columns used in a patsy formula.
Parameters
----------
formula : str, iterable, or dict
Any formula construction supported by ``str_model_expression``.
Returns
-------
columns : list of str
"""
if formula is None:
return []
formula = str_model_expression(formula, add_constant=False)
columns = []
tokens = map(
lambda x: x.extra,
tz.remove(
lambda x: x.extra is None,
_tokens_from_patsy(patsy.parse_formula.parse_formula(formula))))
for tok in tokens:
# if there are parentheses in the expression we
# want to drop them and everything outside
# and start again from the top
if '(' in tok:
start = tok.find('(') + 1
fin = tok.rfind(')')
columns.extend(columns_in_formula(tok[start:fin]))
else:
for toknum, tokval, _, _, _ in generate_tokens(
StringIO(tok).readline):
if toknum == NAME:
columns.append(tokval)
return list(tz.unique(columns)) | python | def columns_in_formula(formula):
"""
Returns the names of all the columns used in a patsy formula.
Parameters
----------
formula : str, iterable, or dict
Any formula construction supported by ``str_model_expression``.
Returns
-------
columns : list of str
"""
if formula is None:
return []
formula = str_model_expression(formula, add_constant=False)
columns = []
tokens = map(
lambda x: x.extra,
tz.remove(
lambda x: x.extra is None,
_tokens_from_patsy(patsy.parse_formula.parse_formula(formula))))
for tok in tokens:
# if there are parentheses in the expression we
# want to drop them and everything outside
# and start again from the top
if '(' in tok:
start = tok.find('(') + 1
fin = tok.rfind(')')
columns.extend(columns_in_formula(tok[start:fin]))
else:
for toknum, tokval, _, _, _ in generate_tokens(
StringIO(tok).readline):
if toknum == NAME:
columns.append(tokval)
return list(tz.unique(columns)) | ['def', 'columns_in_formula', '(', 'formula', ')', ':', 'if', 'formula', 'is', 'None', ':', 'return', '[', ']', 'formula', '=', 'str_model_expression', '(', 'formula', ',', 'add_constant', '=', 'False', ')', 'columns', '=', '[', ']', 'tokens', '=', 'map', '(', 'lambda', 'x', ':', 'x', '.', 'extra', ',', 'tz', '.', 'remove', '(', 'lambda', 'x', ':', 'x', '.', 'extra', 'is', 'None', ',', '_tokens_from_patsy', '(', 'patsy', '.', 'parse_formula', '.', 'parse_formula', '(', 'formula', ')', ')', ')', ')', 'for', 'tok', 'in', 'tokens', ':', '# if there are parentheses in the expression we', '# want to drop them and everything outside', '# and start again from the top', 'if', "'('", 'in', 'tok', ':', 'start', '=', 'tok', '.', 'find', '(', "'('", ')', '+', '1', 'fin', '=', 'tok', '.', 'rfind', '(', "')'", ')', 'columns', '.', 'extend', '(', 'columns_in_formula', '(', 'tok', '[', 'start', ':', 'fin', ']', ')', ')', 'else', ':', 'for', 'toknum', ',', 'tokval', ',', '_', ',', '_', ',', '_', 'in', 'generate_tokens', '(', 'StringIO', '(', 'tok', ')', '.', 'readline', ')', ':', 'if', 'toknum', '==', 'NAME', ':', 'columns', '.', 'append', '(', 'tokval', ')', 'return', 'list', '(', 'tz', '.', 'unique', '(', 'columns', ')', ')'] | Returns the names of all the columns used in a patsy formula.
Parameters
----------
formula : str, iterable, or dict
Any formula construction supported by ``str_model_expression``.
Returns
-------
columns : list of str | ['Returns', 'the', 'names', 'of', 'all', 'the', 'columns', 'used', 'in', 'a', 'patsy', 'formula', '.'] | train | https://github.com/UDST/urbansim/blob/79f815a6503e109f50be270cee92d0f4a34f49ef/urbansim/models/util.py#L307-L347 |
6,228 | rr-/docstring_parser | docstring_parser/parser/google.py | _build_meta | def _build_meta(text: str, title: str) -> DocstringMeta:
"""Build docstring element.
:param text: docstring element text
:param title: title of section containing element
:return:
"""
meta = _sections[title]
if meta == "returns" and ":" not in text.split()[0]:
return DocstringMeta([meta], description=text)
# Split spec and description
before, desc = text.split(":", 1)
if desc:
desc = desc[1:] if desc[0] == " " else desc
if "\n" in desc:
first_line, rest = desc.split("\n", 1)
desc = first_line + "\n" + inspect.cleandoc(rest)
desc = desc.strip("\n")
# Build Meta args
m = re.match(r"(\S+) \((\S+)\)$", before)
if meta == "param" and m:
arg_name, type_name = m.group(1, 2)
args = [meta, type_name, arg_name]
else:
args = [meta, before]
return DocstringMeta(args, description=desc) | python | def _build_meta(text: str, title: str) -> DocstringMeta:
"""Build docstring element.
:param text: docstring element text
:param title: title of section containing element
:return:
"""
meta = _sections[title]
if meta == "returns" and ":" not in text.split()[0]:
return DocstringMeta([meta], description=text)
# Split spec and description
before, desc = text.split(":", 1)
if desc:
desc = desc[1:] if desc[0] == " " else desc
if "\n" in desc:
first_line, rest = desc.split("\n", 1)
desc = first_line + "\n" + inspect.cleandoc(rest)
desc = desc.strip("\n")
# Build Meta args
m = re.match(r"(\S+) \((\S+)\)$", before)
if meta == "param" and m:
arg_name, type_name = m.group(1, 2)
args = [meta, type_name, arg_name]
else:
args = [meta, before]
return DocstringMeta(args, description=desc) | ['def', '_build_meta', '(', 'text', ':', 'str', ',', 'title', ':', 'str', ')', '->', 'DocstringMeta', ':', 'meta', '=', '_sections', '[', 'title', ']', 'if', 'meta', '==', '"returns"', 'and', '":"', 'not', 'in', 'text', '.', 'split', '(', ')', '[', '0', ']', ':', 'return', 'DocstringMeta', '(', '[', 'meta', ']', ',', 'description', '=', 'text', ')', '# Split spec and description', 'before', ',', 'desc', '=', 'text', '.', 'split', '(', '":"', ',', '1', ')', 'if', 'desc', ':', 'desc', '=', 'desc', '[', '1', ':', ']', 'if', 'desc', '[', '0', ']', '==', '" "', 'else', 'desc', 'if', '"\\n"', 'in', 'desc', ':', 'first_line', ',', 'rest', '=', 'desc', '.', 'split', '(', '"\\n"', ',', '1', ')', 'desc', '=', 'first_line', '+', '"\\n"', '+', 'inspect', '.', 'cleandoc', '(', 'rest', ')', 'desc', '=', 'desc', '.', 'strip', '(', '"\\n"', ')', '# Build Meta args', 'm', '=', 're', '.', 'match', '(', 'r"(\\S+) \\((\\S+)\\)$"', ',', 'before', ')', 'if', 'meta', '==', '"param"', 'and', 'm', ':', 'arg_name', ',', 'type_name', '=', 'm', '.', 'group', '(', '1', ',', '2', ')', 'args', '=', '[', 'meta', ',', 'type_name', ',', 'arg_name', ']', 'else', ':', 'args', '=', '[', 'meta', ',', 'before', ']', 'return', 'DocstringMeta', '(', 'args', ',', 'description', '=', 'desc', ')'] | Build docstring element.
:param text: docstring element text
:param title: title of section containing element
:return: | ['Build', 'docstring', 'element', '.'] | train | https://github.com/rr-/docstring_parser/blob/389773f6790a84d33b10160589ce8591122e12bb/docstring_parser/parser/google.py#L28-L57 |
6,229 | Parisson/TimeSide | timeside/core/tools/package.py | check_aubio | def check_aubio():
"Check Aubio availability"
try:
import aubio
except ImportError:
warnings.warn('Aubio librairy is not available', ImportWarning,
stacklevel=2)
_WITH_AUBIO = False
else:
_WITH_AUBIO = True
del aubio
return _WITH_AUBIO | python | def check_aubio():
"Check Aubio availability"
try:
import aubio
except ImportError:
warnings.warn('Aubio librairy is not available', ImportWarning,
stacklevel=2)
_WITH_AUBIO = False
else:
_WITH_AUBIO = True
del aubio
return _WITH_AUBIO | ['def', 'check_aubio', '(', ')', ':', 'try', ':', 'import', 'aubio', 'except', 'ImportError', ':', 'warnings', '.', 'warn', '(', "'Aubio librairy is not available'", ',', 'ImportWarning', ',', 'stacklevel', '=', '2', ')', '_WITH_AUBIO', '=', 'False', 'else', ':', '_WITH_AUBIO', '=', 'True', 'del', 'aubio', 'return', '_WITH_AUBIO'] | Check Aubio availability | ['Check', 'Aubio', 'availability'] | train | https://github.com/Parisson/TimeSide/blob/0618d75cd2f16021afcfd3d5b77f692adad76ea5/timeside/core/tools/package.py#L86-L98 |
6,230 | econ-ark/HARK | HARK/interpolation.py | HARKinterpolator4D.derivativeW | def derivativeW(self,w,x,y,z):
'''
Evaluates the partial derivative with respect to w (the first argument)
of the interpolated function at the given input.
Parameters
----------
w : np.array or float
Real values to be evaluated in the interpolated function.
x : np.array or float
Real values to be evaluated in the interpolated function; must be
the same size as w.
y : np.array or float
Real values to be evaluated in the interpolated function; must be
the same size as w.
z : np.array or float
Real values to be evaluated in the interpolated function; must be
the same size as w.
Returns
-------
dfdw : np.array or float
The derivative with respect to w of the interpolated function eval-
uated at w,x,y,z: dfdw = f_w(w,x,y,z), with the same shape as inputs.
'''
wa = np.asarray(w)
xa = np.asarray(x)
ya = np.asarray(y)
za = np.asarray(z)
return (self._derW(wa.flatten(),xa.flatten(),ya.flatten(),za.flatten())).reshape(wa.shape) | python | def derivativeW(self,w,x,y,z):
'''
Evaluates the partial derivative with respect to w (the first argument)
of the interpolated function at the given input.
Parameters
----------
w : np.array or float
Real values to be evaluated in the interpolated function.
x : np.array or float
Real values to be evaluated in the interpolated function; must be
the same size as w.
y : np.array or float
Real values to be evaluated in the interpolated function; must be
the same size as w.
z : np.array or float
Real values to be evaluated in the interpolated function; must be
the same size as w.
Returns
-------
dfdw : np.array or float
The derivative with respect to w of the interpolated function eval-
uated at w,x,y,z: dfdw = f_w(w,x,y,z), with the same shape as inputs.
'''
wa = np.asarray(w)
xa = np.asarray(x)
ya = np.asarray(y)
za = np.asarray(z)
return (self._derW(wa.flatten(),xa.flatten(),ya.flatten(),za.flatten())).reshape(wa.shape) | ['def', 'derivativeW', '(', 'self', ',', 'w', ',', 'x', ',', 'y', ',', 'z', ')', ':', 'wa', '=', 'np', '.', 'asarray', '(', 'w', ')', 'xa', '=', 'np', '.', 'asarray', '(', 'x', ')', 'ya', '=', 'np', '.', 'asarray', '(', 'y', ')', 'za', '=', 'np', '.', 'asarray', '(', 'z', ')', 'return', '(', 'self', '.', '_derW', '(', 'wa', '.', 'flatten', '(', ')', ',', 'xa', '.', 'flatten', '(', ')', ',', 'ya', '.', 'flatten', '(', ')', ',', 'za', '.', 'flatten', '(', ')', ')', ')', '.', 'reshape', '(', 'wa', '.', 'shape', ')'] | Evaluates the partial derivative with respect to w (the first argument)
of the interpolated function at the given input.
Parameters
----------
w : np.array or float
Real values to be evaluated in the interpolated function.
x : np.array or float
Real values to be evaluated in the interpolated function; must be
the same size as w.
y : np.array or float
Real values to be evaluated in the interpolated function; must be
the same size as w.
z : np.array or float
Real values to be evaluated in the interpolated function; must be
the same size as w.
Returns
-------
dfdw : np.array or float
The derivative with respect to w of the interpolated function eval-
uated at w,x,y,z: dfdw = f_w(w,x,y,z), with the same shape as inputs. | ['Evaluates', 'the', 'partial', 'derivative', 'with', 'respect', 'to', 'w', '(', 'the', 'first', 'argument', ')', 'of', 'the', 'interpolated', 'function', 'at', 'the', 'given', 'input', '.'] | train | https://github.com/econ-ark/HARK/blob/3d184153a189e618a87c9540df1cd12044039cc5/HARK/interpolation.py#L383-L412 |
6,231 | sdss/sdss_access | python/sdss_access/path/path.py | BasePath.location | def location(self, filetype, base_dir=None, **kwargs):
"""Return the location of the relative sas path of a given type of file.
Parameters
----------
filetype : str
File type parameter.
Returns
-------
full : str
The relative sas path to the file.
"""
full = kwargs.get('full', None)
if not full:
full = self.full(filetype, **kwargs)
self.set_base_dir(base_dir=base_dir)
location = full[len(self.base_dir):] if full and full.startswith(self.base_dir) else None
if location and '//' in location:
location = location.replace('//', '/')
return location | python | def location(self, filetype, base_dir=None, **kwargs):
"""Return the location of the relative sas path of a given type of file.
Parameters
----------
filetype : str
File type parameter.
Returns
-------
full : str
The relative sas path to the file.
"""
full = kwargs.get('full', None)
if not full:
full = self.full(filetype, **kwargs)
self.set_base_dir(base_dir=base_dir)
location = full[len(self.base_dir):] if full and full.startswith(self.base_dir) else None
if location and '//' in location:
location = location.replace('//', '/')
return location | ['def', 'location', '(', 'self', ',', 'filetype', ',', 'base_dir', '=', 'None', ',', '*', '*', 'kwargs', ')', ':', 'full', '=', 'kwargs', '.', 'get', '(', "'full'", ',', 'None', ')', 'if', 'not', 'full', ':', 'full', '=', 'self', '.', 'full', '(', 'filetype', ',', '*', '*', 'kwargs', ')', 'self', '.', 'set_base_dir', '(', 'base_dir', '=', 'base_dir', ')', 'location', '=', 'full', '[', 'len', '(', 'self', '.', 'base_dir', ')', ':', ']', 'if', 'full', 'and', 'full', '.', 'startswith', '(', 'self', '.', 'base_dir', ')', 'else', 'None', 'if', 'location', 'and', "'//'", 'in', 'location', ':', 'location', '=', 'location', '.', 'replace', '(', "'//'", ',', "'/'", ')', 'return', 'location'] | Return the location of the relative sas path of a given type of file.
Parameters
----------
filetype : str
File type parameter.
Returns
-------
full : str
The relative sas path to the file. | ['Return', 'the', 'location', 'of', 'the', 'relative', 'sas', 'path', 'of', 'a', 'given', 'type', 'of', 'file', '.'] | train | https://github.com/sdss/sdss_access/blob/76375bbf37d39d2e4ccbed90bdfa9a4298784470/python/sdss_access/path/path.py#L584-L608 |
6,232 | mitsei/dlkit | dlkit/handcar/relationship/managers.py | RelationshipProxyManager.get_relationship_query_session_for_family | def get_relationship_query_session_for_family(self, family_id=None, proxy=None):
"""Gets the ``OsidSession`` associated with the relationship query service for the given family.
arg: family_id (osid.id.Id): the ``Id`` of the family
arg: proxy (osid.proxy.Proxy): a proxy
return: (osid.relationship.RelationshipQuerySession) - a
``RelationshipQuerySession``
raise: NotFound - no ``Family`` found by the given ``Id``
raise: NullArgument - ``family_id`` or ``proxy`` is ``null``
raise: OperationFailed - unable to complete request
raise: Unimplemented - ``supports_relationship_query()`` or
``supports_visible_federation()`` is ``false``
*compliance: optional -- This method must be implemented if ``supports_relationship_query()``
and ``supports_visible_federation()`` are ``true``*
"""
if not family_id:
raise NullArgument
if not self.supports_relationship_query():
raise Unimplemented()
##
# Need to include check to see if the familyId is found otherwise raise NotFound
##
try:
from . import sessions
except ImportError:
raise OperationFailed()
proxy = self._convert_proxy(proxy)
try:
session = sessions.RelationshipQuerySession(family_id, proxy=proxy, runtime=self._runtime)
except AttributeError:
raise OperationFailed()
return session | python | def get_relationship_query_session_for_family(self, family_id=None, proxy=None):
"""Gets the ``OsidSession`` associated with the relationship query service for the given family.
arg: family_id (osid.id.Id): the ``Id`` of the family
arg: proxy (osid.proxy.Proxy): a proxy
return: (osid.relationship.RelationshipQuerySession) - a
``RelationshipQuerySession``
raise: NotFound - no ``Family`` found by the given ``Id``
raise: NullArgument - ``family_id`` or ``proxy`` is ``null``
raise: OperationFailed - unable to complete request
raise: Unimplemented - ``supports_relationship_query()`` or
``supports_visible_federation()`` is ``false``
*compliance: optional -- This method must be implemented if ``supports_relationship_query()``
and ``supports_visible_federation()`` are ``true``*
"""
if not family_id:
raise NullArgument
if not self.supports_relationship_query():
raise Unimplemented()
##
# Need to include check to see if the familyId is found otherwise raise NotFound
##
try:
from . import sessions
except ImportError:
raise OperationFailed()
proxy = self._convert_proxy(proxy)
try:
session = sessions.RelationshipQuerySession(family_id, proxy=proxy, runtime=self._runtime)
except AttributeError:
raise OperationFailed()
return session | ['def', 'get_relationship_query_session_for_family', '(', 'self', ',', 'family_id', '=', 'None', ',', 'proxy', '=', 'None', ')', ':', 'if', 'not', 'family_id', ':', 'raise', 'NullArgument', 'if', 'not', 'self', '.', 'supports_relationship_query', '(', ')', ':', 'raise', 'Unimplemented', '(', ')', '##', '# Need to include check to see if the familyId is found otherwise raise NotFound', '##', 'try', ':', 'from', '.', 'import', 'sessions', 'except', 'ImportError', ':', 'raise', 'OperationFailed', '(', ')', 'proxy', '=', 'self', '.', '_convert_proxy', '(', 'proxy', ')', 'try', ':', 'session', '=', 'sessions', '.', 'RelationshipQuerySession', '(', 'family_id', ',', 'proxy', '=', 'proxy', ',', 'runtime', '=', 'self', '.', '_runtime', ')', 'except', 'AttributeError', ':', 'raise', 'OperationFailed', '(', ')', 'return', 'session'] | Gets the ``OsidSession`` associated with the relationship query service for the given family.
arg: family_id (osid.id.Id): the ``Id`` of the family
arg: proxy (osid.proxy.Proxy): a proxy
return: (osid.relationship.RelationshipQuerySession) - a
``RelationshipQuerySession``
raise: NotFound - no ``Family`` found by the given ``Id``
raise: NullArgument - ``family_id`` or ``proxy`` is ``null``
raise: OperationFailed - unable to complete request
raise: Unimplemented - ``supports_relationship_query()`` or
``supports_visible_federation()`` is ``false``
*compliance: optional -- This method must be implemented if ``supports_relationship_query()``
and ``supports_visible_federation()`` are ``true``* | ['Gets', 'the', 'OsidSession', 'associated', 'with', 'the', 'relationship', 'query', 'service', 'for', 'the', 'given', 'family', '.'] | train | https://github.com/mitsei/dlkit/blob/445f968a175d61c8d92c0f617a3c17dc1dc7c584/dlkit/handcar/relationship/managers.py#L985-L1017 |
6,233 | michal-stuglik/django-blastplus | blastplus/features/record.py | Alignment.get_id | def get_id(self):
"""Returns unique id of an alignment. """
return hash(str(self.title) + str(self.best_score()) + str(self.hit_def)) | python | def get_id(self):
"""Returns unique id of an alignment. """
return hash(str(self.title) + str(self.best_score()) + str(self.hit_def)) | ['def', 'get_id', '(', 'self', ')', ':', 'return', 'hash', '(', 'str', '(', 'self', '.', 'title', ')', '+', 'str', '(', 'self', '.', 'best_score', '(', ')', ')', '+', 'str', '(', 'self', '.', 'hit_def', ')', ')'] | Returns unique id of an alignment. | ['Returns', 'unique', 'id', 'of', 'an', 'alignment', '.'] | train | https://github.com/michal-stuglik/django-blastplus/blob/4f5e15fb9f8069c3bed5f8fd941c4b9891daad4b/blastplus/features/record.py#L119-L121 |
6,234 | twisted/axiom | axiom/userbase.py | insertUserStore | def insertUserStore(siteStore, userStorePath):
"""
Move the SubStore at the indicated location into the given site store's
directory and then hook it up to the site store's authentication database.
@type siteStore: C{Store}
@type userStorePath: C{FilePath}
"""
# The following may, but does not need to be in a transaction, because it
# is merely an attempt to guess a reasonable filesystem name to use for
# this avatar. The user store being operated on is expected to be used
# exclusively by this process.
ls = siteStore.findUnique(LoginSystem)
unattachedSubStore = Store(userStorePath)
for lm in unattachedSubStore.query(LoginMethod,
LoginMethod.account == unattachedSubStore.findUnique(LoginAccount),
sort=LoginMethod.internal.descending):
if ls.accountByAddress(lm.localpart, lm.domain) is None:
localpart, domain = lm.localpart, lm.domain
break
else:
raise AllNamesConflict()
unattachedSubStore.close()
insertLocation = siteStore.newFilePath('account', domain, localpart + '.axiom')
insertParentLoc = insertLocation.parent()
if not insertParentLoc.exists():
insertParentLoc.makedirs()
if insertLocation.exists():
raise DatabaseDirectoryConflict()
userStorePath.moveTo(insertLocation)
ss = SubStore(store=siteStore, storepath=insertLocation)
attachedStore = ss.open()
# migrateUp() manages its own transactions because it interacts with two
# different stores.
attachedStore.findUnique(LoginAccount).migrateUp() | python | def insertUserStore(siteStore, userStorePath):
"""
Move the SubStore at the indicated location into the given site store's
directory and then hook it up to the site store's authentication database.
@type siteStore: C{Store}
@type userStorePath: C{FilePath}
"""
# The following may, but does not need to be in a transaction, because it
# is merely an attempt to guess a reasonable filesystem name to use for
# this avatar. The user store being operated on is expected to be used
# exclusively by this process.
ls = siteStore.findUnique(LoginSystem)
unattachedSubStore = Store(userStorePath)
for lm in unattachedSubStore.query(LoginMethod,
LoginMethod.account == unattachedSubStore.findUnique(LoginAccount),
sort=LoginMethod.internal.descending):
if ls.accountByAddress(lm.localpart, lm.domain) is None:
localpart, domain = lm.localpart, lm.domain
break
else:
raise AllNamesConflict()
unattachedSubStore.close()
insertLocation = siteStore.newFilePath('account', domain, localpart + '.axiom')
insertParentLoc = insertLocation.parent()
if not insertParentLoc.exists():
insertParentLoc.makedirs()
if insertLocation.exists():
raise DatabaseDirectoryConflict()
userStorePath.moveTo(insertLocation)
ss = SubStore(store=siteStore, storepath=insertLocation)
attachedStore = ss.open()
# migrateUp() manages its own transactions because it interacts with two
# different stores.
attachedStore.findUnique(LoginAccount).migrateUp() | ['def', 'insertUserStore', '(', 'siteStore', ',', 'userStorePath', ')', ':', '# The following may, but does not need to be in a transaction, because it', '# is merely an attempt to guess a reasonable filesystem name to use for', '# this avatar. The user store being operated on is expected to be used', '# exclusively by this process.', 'ls', '=', 'siteStore', '.', 'findUnique', '(', 'LoginSystem', ')', 'unattachedSubStore', '=', 'Store', '(', 'userStorePath', ')', 'for', 'lm', 'in', 'unattachedSubStore', '.', 'query', '(', 'LoginMethod', ',', 'LoginMethod', '.', 'account', '==', 'unattachedSubStore', '.', 'findUnique', '(', 'LoginAccount', ')', ',', 'sort', '=', 'LoginMethod', '.', 'internal', '.', 'descending', ')', ':', 'if', 'ls', '.', 'accountByAddress', '(', 'lm', '.', 'localpart', ',', 'lm', '.', 'domain', ')', 'is', 'None', ':', 'localpart', ',', 'domain', '=', 'lm', '.', 'localpart', ',', 'lm', '.', 'domain', 'break', 'else', ':', 'raise', 'AllNamesConflict', '(', ')', 'unattachedSubStore', '.', 'close', '(', ')', 'insertLocation', '=', 'siteStore', '.', 'newFilePath', '(', "'account'", ',', 'domain', ',', 'localpart', '+', "'.axiom'", ')', 'insertParentLoc', '=', 'insertLocation', '.', 'parent', '(', ')', 'if', 'not', 'insertParentLoc', '.', 'exists', '(', ')', ':', 'insertParentLoc', '.', 'makedirs', '(', ')', 'if', 'insertLocation', '.', 'exists', '(', ')', ':', 'raise', 'DatabaseDirectoryConflict', '(', ')', 'userStorePath', '.', 'moveTo', '(', 'insertLocation', ')', 'ss', '=', 'SubStore', '(', 'store', '=', 'siteStore', ',', 'storepath', '=', 'insertLocation', ')', 'attachedStore', '=', 'ss', '.', 'open', '(', ')', '# migrateUp() manages its own transactions because it interacts with two', '# different stores.', 'attachedStore', '.', 'findUnique', '(', 'LoginAccount', ')', '.', 'migrateUp', '(', ')'] | Move the SubStore at the indicated location into the given site store's
directory and then hook it up to the site store's authentication database.
@type siteStore: C{Store}
@type userStorePath: C{FilePath} | ['Move', 'the', 'SubStore', 'at', 'the', 'indicated', 'location', 'into', 'the', 'given', 'site', 'store', 's', 'directory', 'and', 'then', 'hook', 'it', 'up', 'to', 'the', 'site', 'store', 's', 'authentication', 'database', '.'] | train | https://github.com/twisted/axiom/blob/7de70bc8fe1bb81f9c2339fba8daec9eb2e92b68/axiom/userbase.py#L306-L342 |
6,235 | hannes-brt/hebel | hebel/pycuda_ops/cublas.py | cublasCtpsv | def cublasCtpsv(handle, uplo, trans, diag, n, AP, x, incx):
"""
Solve complex triangular-packed system with one right-hand side.
"""
status = _libcublas.cublasCtpsv_v2(handle,
_CUBLAS_FILL_MODE[uplo],
_CUBLAS_OP[trans],
_CUBLAS_DIAG[diag],
n, int(AP), int(x), incx)
cublasCheckStatus(status) | python | def cublasCtpsv(handle, uplo, trans, diag, n, AP, x, incx):
"""
Solve complex triangular-packed system with one right-hand side.
"""
status = _libcublas.cublasCtpsv_v2(handle,
_CUBLAS_FILL_MODE[uplo],
_CUBLAS_OP[trans],
_CUBLAS_DIAG[diag],
n, int(AP), int(x), incx)
cublasCheckStatus(status) | ['def', 'cublasCtpsv', '(', 'handle', ',', 'uplo', ',', 'trans', ',', 'diag', ',', 'n', ',', 'AP', ',', 'x', ',', 'incx', ')', ':', 'status', '=', '_libcublas', '.', 'cublasCtpsv_v2', '(', 'handle', ',', '_CUBLAS_FILL_MODE', '[', 'uplo', ']', ',', '_CUBLAS_OP', '[', 'trans', ']', ',', '_CUBLAS_DIAG', '[', 'diag', ']', ',', 'n', ',', 'int', '(', 'AP', ')', ',', 'int', '(', 'x', ')', ',', 'incx', ')', 'cublasCheckStatus', '(', 'status', ')'] | Solve complex triangular-packed system with one right-hand side. | ['Solve', 'complex', 'triangular', '-', 'packed', 'system', 'with', 'one', 'right', '-', 'hand', 'side', '.'] | train | https://github.com/hannes-brt/hebel/blob/1e2c3a9309c2646103901b26a55be4e312dd5005/hebel/pycuda_ops/cublas.py#L3328-L3339 |
6,236 | scivision/msise00 | msise00/base.py | run | def run(time: datetime, altkm: float,
glat: Union[float, np.ndarray], glon: Union[float, np.ndarray], *,
f107a: float = None, f107: float = None, Ap: int = None) -> xarray.Dataset:
"""
loops the rungtd1d function below. Figure it's easier to troubleshoot in Python than Fortran.
"""
glat = np.atleast_2d(glat)
glon = np.atleast_2d(glon) # has to be here
# %% altitude 1-D
if glat.size == 1 and glon.size == 1 and isinstance(time, (str, date, datetime, np.datetime64)):
atmos = rungtd1d(time, altkm, glat.squeeze()[()], glon.squeeze()[()],
f107a=f107a, f107=f107, Ap=Ap)
# %% lat/lon grid at 1 altitude
else:
atmos = loopalt_gtd(time, glat, glon, altkm,
f107a=f107a, f107=f107, Ap=Ap)
return atmos | python | def run(time: datetime, altkm: float,
glat: Union[float, np.ndarray], glon: Union[float, np.ndarray], *,
f107a: float = None, f107: float = None, Ap: int = None) -> xarray.Dataset:
"""
loops the rungtd1d function below. Figure it's easier to troubleshoot in Python than Fortran.
"""
glat = np.atleast_2d(glat)
glon = np.atleast_2d(glon) # has to be here
# %% altitude 1-D
if glat.size == 1 and glon.size == 1 and isinstance(time, (str, date, datetime, np.datetime64)):
atmos = rungtd1d(time, altkm, glat.squeeze()[()], glon.squeeze()[()],
f107a=f107a, f107=f107, Ap=Ap)
# %% lat/lon grid at 1 altitude
else:
atmos = loopalt_gtd(time, glat, glon, altkm,
f107a=f107a, f107=f107, Ap=Ap)
return atmos | ['def', 'run', '(', 'time', ':', 'datetime', ',', 'altkm', ':', 'float', ',', 'glat', ':', 'Union', '[', 'float', ',', 'np', '.', 'ndarray', ']', ',', 'glon', ':', 'Union', '[', 'float', ',', 'np', '.', 'ndarray', ']', ',', '*', ',', 'f107a', ':', 'float', '=', 'None', ',', 'f107', ':', 'float', '=', 'None', ',', 'Ap', ':', 'int', '=', 'None', ')', '->', 'xarray', '.', 'Dataset', ':', 'glat', '=', 'np', '.', 'atleast_2d', '(', 'glat', ')', 'glon', '=', 'np', '.', 'atleast_2d', '(', 'glon', ')', '# has to be here', '# %% altitude 1-D', 'if', 'glat', '.', 'size', '==', '1', 'and', 'glon', '.', 'size', '==', '1', 'and', 'isinstance', '(', 'time', ',', '(', 'str', ',', 'date', ',', 'datetime', ',', 'np', '.', 'datetime64', ')', ')', ':', 'atmos', '=', 'rungtd1d', '(', 'time', ',', 'altkm', ',', 'glat', '.', 'squeeze', '(', ')', '[', '(', ')', ']', ',', 'glon', '.', 'squeeze', '(', ')', '[', '(', ')', ']', ',', 'f107a', '=', 'f107a', ',', 'f107', '=', 'f107', ',', 'Ap', '=', 'Ap', ')', '# %% lat/lon grid at 1 altitude', 'else', ':', 'atmos', '=', 'loopalt_gtd', '(', 'time', ',', 'glat', ',', 'glon', ',', 'altkm', ',', 'f107a', '=', 'f107a', ',', 'f107', '=', 'f107', ',', 'Ap', '=', 'Ap', ')', 'return', 'atmos'] | loops the rungtd1d function below. Figure it's easier to troubleshoot in Python than Fortran. | ['loops', 'the', 'rungtd1d', 'function', 'below', '.', 'Figure', 'it', 's', 'easier', 'to', 'troubleshoot', 'in', 'Python', 'than', 'Fortran', '.'] | train | https://github.com/scivision/msise00/blob/13a283ec02679ab74672f284ba68a7a8f896dc6f/msise00/base.py#L34-L51 |
6,237 | MrYsLab/pymata-aio | pymata_aio/pymata3.py | PyMata3.set_analog_latch | def set_analog_latch(self, pin, threshold_type, threshold_value,
cb=None, cb_type=None):
"""
This method "arms" an analog pin for its data to be latched and
saved in the latching table.
If a callback method is provided, when latching criteria is achieved,
the callback function is called with latching data notification.
:param pin: Analog pin number (value following an 'A' designator,
i.e. A5 = 5
:param threshold_type: Constants.LATCH_GT | Constants.LATCH_LT |
Constants.LATCH_GTE | Constants.LATCH_LTE
:param threshold_value: numerical value - between 0 and 1023
:param cb: callback method
:param cb_type: Constants.CB_TYPE_DIRECT = direct call or
Constants.CB_TYPE_ASYNCIO = asyncio coroutine
:returns: True if successful, False if parameter data is invalid
"""
task = asyncio.ensure_future(self.core.set_analog_latch(pin, threshold_type, threshold_value, cb, cb_type))
result = self.loop.run_until_complete(task)
return result | python | def set_analog_latch(self, pin, threshold_type, threshold_value,
cb=None, cb_type=None):
"""
This method "arms" an analog pin for its data to be latched and
saved in the latching table.
If a callback method is provided, when latching criteria is achieved,
the callback function is called with latching data notification.
:param pin: Analog pin number (value following an 'A' designator,
i.e. A5 = 5
:param threshold_type: Constants.LATCH_GT | Constants.LATCH_LT |
Constants.LATCH_GTE | Constants.LATCH_LTE
:param threshold_value: numerical value - between 0 and 1023
:param cb: callback method
:param cb_type: Constants.CB_TYPE_DIRECT = direct call or
Constants.CB_TYPE_ASYNCIO = asyncio coroutine
:returns: True if successful, False if parameter data is invalid
"""
task = asyncio.ensure_future(self.core.set_analog_latch(pin, threshold_type, threshold_value, cb, cb_type))
result = self.loop.run_until_complete(task)
return result | ['def', 'set_analog_latch', '(', 'self', ',', 'pin', ',', 'threshold_type', ',', 'threshold_value', ',', 'cb', '=', 'None', ',', 'cb_type', '=', 'None', ')', ':', 'task', '=', 'asyncio', '.', 'ensure_future', '(', 'self', '.', 'core', '.', 'set_analog_latch', '(', 'pin', ',', 'threshold_type', ',', 'threshold_value', ',', 'cb', ',', 'cb_type', ')', ')', 'result', '=', 'self', '.', 'loop', '.', 'run_until_complete', '(', 'task', ')', 'return', 'result'] | This method "arms" an analog pin for its data to be latched and
saved in the latching table.
If a callback method is provided, when latching criteria is achieved,
the callback function is called with latching data notification.
:param pin: Analog pin number (value following an 'A' designator,
i.e. A5 = 5
:param threshold_type: Constants.LATCH_GT | Constants.LATCH_LT |
Constants.LATCH_GTE | Constants.LATCH_LTE
:param threshold_value: numerical value - between 0 and 1023
:param cb: callback method
:param cb_type: Constants.CB_TYPE_DIRECT = direct call or
Constants.CB_TYPE_ASYNCIO = asyncio coroutine
:returns: True if successful, False if parameter data is invalid | ['This', 'method', 'arms', 'an', 'analog', 'pin', 'for', 'its', 'data', 'to', 'be', 'latched', 'and', 'saved', 'in', 'the', 'latching', 'table', '.', 'If', 'a', 'callback', 'method', 'is', 'provided', 'when', 'latching', 'criteria', 'is', 'achieved', 'the', 'callback', 'function', 'is', 'called', 'with', 'latching', 'data', 'notification', '.'] | train | https://github.com/MrYsLab/pymata-aio/blob/015081a4628b9d47dfe3f8d6c698ff903f107810/pymata_aio/pymata3.py#L524-L550 |
6,238 | ihmeuw/vivarium | src/vivarium/config_tree.py | ConfigNode.drop_layer | def drop_layer(self, layer):
"""Removes the named layer and the value associated with it from the node.
Parameters
----------
layer : str
Name of the layer to drop.
Raises
------
TypeError
If the node is frozen
KeyError
If the named layer does not exist
"""
if self._frozen:
raise TypeError('Frozen ConfigNode does not support modification')
self.reset_layer(layer)
self._layers.remove(layer) | python | def drop_layer(self, layer):
"""Removes the named layer and the value associated with it from the node.
Parameters
----------
layer : str
Name of the layer to drop.
Raises
------
TypeError
If the node is frozen
KeyError
If the named layer does not exist
"""
if self._frozen:
raise TypeError('Frozen ConfigNode does not support modification')
self.reset_layer(layer)
self._layers.remove(layer) | ['def', 'drop_layer', '(', 'self', ',', 'layer', ')', ':', 'if', 'self', '.', '_frozen', ':', 'raise', 'TypeError', '(', "'Frozen ConfigNode does not support modification'", ')', 'self', '.', 'reset_layer', '(', 'layer', ')', 'self', '.', '_layers', '.', 'remove', '(', 'layer', ')'] | Removes the named layer and the value associated with it from the node.
Parameters
----------
layer : str
Name of the layer to drop.
Raises
------
TypeError
If the node is frozen
KeyError
If the named layer does not exist | ['Removes', 'the', 'named', 'layer', 'and', 'the', 'value', 'associated', 'with', 'it', 'from', 'the', 'node', '.'] | train | https://github.com/ihmeuw/vivarium/blob/c5f5d50f775c8bf337d3aae1ff7c57c025a8e258/src/vivarium/config_tree.py#L148-L166 |
6,239 | wrongwaycn/ssdb-py | ssdb/connection.py | PythonParser.on_connect | def on_connect(self, connection):
"""
Called when the socket connects
"""
self._sock = connection._sock
self._buffer = SocketBuffer(self._sock, self.socket_read_size)
if connection.decode_responses:
self.encoding = connection.encoding | python | def on_connect(self, connection):
"""
Called when the socket connects
"""
self._sock = connection._sock
self._buffer = SocketBuffer(self._sock, self.socket_read_size)
if connection.decode_responses:
self.encoding = connection.encoding | ['def', 'on_connect', '(', 'self', ',', 'connection', ')', ':', 'self', '.', '_sock', '=', 'connection', '.', '_sock', 'self', '.', '_buffer', '=', 'SocketBuffer', '(', 'self', '.', '_sock', ',', 'self', '.', 'socket_read_size', ')', 'if', 'connection', '.', 'decode_responses', ':', 'self', '.', 'encoding', '=', 'connection', '.', 'encoding'] | Called when the socket connects | ['Called', 'when', 'the', 'socket', 'connects'] | train | https://github.com/wrongwaycn/ssdb-py/blob/ce7b1542f0faa06fe71a60c667fe15992af0f621/ssdb/connection.py#L171-L178 |
6,240 | a10networks/acos-client | acos_client/v30/device_context.py | DeviceContext.switch | def switch(self, device_id, obj_slot_id):
"""Switching of device-context"""
payload = {
"device-context": self._build_payload(device_id, obj_slot_id)
}
return self._post(self.url_prefix, payload) | python | def switch(self, device_id, obj_slot_id):
"""Switching of device-context"""
payload = {
"device-context": self._build_payload(device_id, obj_slot_id)
}
return self._post(self.url_prefix, payload) | ['def', 'switch', '(', 'self', ',', 'device_id', ',', 'obj_slot_id', ')', ':', 'payload', '=', '{', '"device-context"', ':', 'self', '.', '_build_payload', '(', 'device_id', ',', 'obj_slot_id', ')', '}', 'return', 'self', '.', '_post', '(', 'self', '.', 'url_prefix', ',', 'payload', ')'] | Switching of device-context | ['Switching', 'of', 'device', '-', 'context'] | train | https://github.com/a10networks/acos-client/blob/14d1fff589650650c9a65047d54c6c8c1d6b75f2/acos_client/v30/device_context.py#L24-L30 |
6,241 | EconForge/dolo | dolo/algos/value_iteration.py | evaluate_policy | def evaluate_policy(model,
mdr,
tol=1e-8,
maxit=2000,
grid={},
verbose=True,
initial_guess=None,
hook=None,
integration_orders=None,
details=False,
interp_type='cubic'):
"""Compute value function corresponding to policy ``dr``
Parameters:
-----------
model:
"dtcscc" model. Must contain a 'value' function.
mdr:
decision rule to evaluate
Returns:
--------
decision rule:
value function (a function of the space similar to a decision rule
object)
"""
process = model.exogenous
dprocess = process.discretize()
n_ms = dprocess.n_nodes() # number of exogenous states
n_mv = dprocess.n_inodes(
0) # this assume number of integration nodes is constant
x0 = model.calibration['controls']
v0 = model.calibration['values']
parms = model.calibration['parameters']
n_x = len(x0)
n_v = len(v0)
n_s = len(model.symbols['states'])
endo_grid = model.get_grid(**grid)
exo_grid = dprocess.grid
if initial_guess is not None:
mdrv = initial_guess
else:
mdrv = DecisionRule(exo_grid, endo_grid, interp_type=interp_type)
grid = mdrv.endo_grid.nodes()
N = grid.shape[0]
if isinstance(mdr, np.ndarray):
controls = mdr
else:
controls = np.zeros((n_ms, N, n_x))
for i_m in range(n_ms):
controls[i_m, :, :] = mdr.eval_is(i_m, grid)
values_0 = np.zeros((n_ms, N, n_v))
if initial_guess is None:
for i_m in range(n_ms):
values_0[i_m, :, :] = v0[None, :]
else:
for i_m in range(n_ms):
values_0[i_m, :, :] = initial_guess.eval_is(i_m, grid)
val = model.functions['value']
g = model.functions['transition']
sh_v = values_0.shape
err = 10
inner_maxit = 50
it = 0
if verbose:
headline = '|{0:^4} | {1:10} | {2:8} | {3:8} |'.format(
'N', ' Error', 'Gain', 'Time')
stars = '-' * len(headline)
print(stars)
print(headline)
print(stars)
t1 = time.time()
err_0 = np.nan
verbit = (verbose == 'full')
while err > tol and it < maxit:
it += 1
t_start = time.time()
mdrv.set_values(values_0.reshape(sh_v))
values = update_value(val, g, grid, controls, values_0, mdr, mdrv,
dprocess, parms).reshape((-1, n_v))
err = abs(values.reshape(sh_v) - values_0).max()
err_SA = err / err_0
err_0 = err
values_0 = values.reshape(sh_v)
t_finish = time.time()
elapsed = t_finish - t_start
if verbose:
print('|{0:4} | {1:10.3e} | {2:8.3f} | {3:8.3f} |'.format(
it, err, err_SA, elapsed))
# values_0 = values.reshape(sh_v)
t2 = time.time()
if verbose:
print(stars)
print("Elapsed: {} seconds.".format(t2 - t1))
print(stars)
if not details:
return mdrv
else:
return EvaluationResult(mdrv, it, tol, err) | python | def evaluate_policy(model,
mdr,
tol=1e-8,
maxit=2000,
grid={},
verbose=True,
initial_guess=None,
hook=None,
integration_orders=None,
details=False,
interp_type='cubic'):
"""Compute value function corresponding to policy ``dr``
Parameters:
-----------
model:
"dtcscc" model. Must contain a 'value' function.
mdr:
decision rule to evaluate
Returns:
--------
decision rule:
value function (a function of the space similar to a decision rule
object)
"""
process = model.exogenous
dprocess = process.discretize()
n_ms = dprocess.n_nodes() # number of exogenous states
n_mv = dprocess.n_inodes(
0) # this assume number of integration nodes is constant
x0 = model.calibration['controls']
v0 = model.calibration['values']
parms = model.calibration['parameters']
n_x = len(x0)
n_v = len(v0)
n_s = len(model.symbols['states'])
endo_grid = model.get_grid(**grid)
exo_grid = dprocess.grid
if initial_guess is not None:
mdrv = initial_guess
else:
mdrv = DecisionRule(exo_grid, endo_grid, interp_type=interp_type)
grid = mdrv.endo_grid.nodes()
N = grid.shape[0]
if isinstance(mdr, np.ndarray):
controls = mdr
else:
controls = np.zeros((n_ms, N, n_x))
for i_m in range(n_ms):
controls[i_m, :, :] = mdr.eval_is(i_m, grid)
values_0 = np.zeros((n_ms, N, n_v))
if initial_guess is None:
for i_m in range(n_ms):
values_0[i_m, :, :] = v0[None, :]
else:
for i_m in range(n_ms):
values_0[i_m, :, :] = initial_guess.eval_is(i_m, grid)
val = model.functions['value']
g = model.functions['transition']
sh_v = values_0.shape
err = 10
inner_maxit = 50
it = 0
if verbose:
headline = '|{0:^4} | {1:10} | {2:8} | {3:8} |'.format(
'N', ' Error', 'Gain', 'Time')
stars = '-' * len(headline)
print(stars)
print(headline)
print(stars)
t1 = time.time()
err_0 = np.nan
verbit = (verbose == 'full')
while err > tol and it < maxit:
it += 1
t_start = time.time()
mdrv.set_values(values_0.reshape(sh_v))
values = update_value(val, g, grid, controls, values_0, mdr, mdrv,
dprocess, parms).reshape((-1, n_v))
err = abs(values.reshape(sh_v) - values_0).max()
err_SA = err / err_0
err_0 = err
values_0 = values.reshape(sh_v)
t_finish = time.time()
elapsed = t_finish - t_start
if verbose:
print('|{0:4} | {1:10.3e} | {2:8.3f} | {3:8.3f} |'.format(
it, err, err_SA, elapsed))
# values_0 = values.reshape(sh_v)
t2 = time.time()
if verbose:
print(stars)
print("Elapsed: {} seconds.".format(t2 - t1))
print(stars)
if not details:
return mdrv
else:
return EvaluationResult(mdrv, it, tol, err) | ['def', 'evaluate_policy', '(', 'model', ',', 'mdr', ',', 'tol', '=', '1e-8', ',', 'maxit', '=', '2000', ',', 'grid', '=', '{', '}', ',', 'verbose', '=', 'True', ',', 'initial_guess', '=', 'None', ',', 'hook', '=', 'None', ',', 'integration_orders', '=', 'None', ',', 'details', '=', 'False', ',', 'interp_type', '=', "'cubic'", ')', ':', 'process', '=', 'model', '.', 'exogenous', 'dprocess', '=', 'process', '.', 'discretize', '(', ')', 'n_ms', '=', 'dprocess', '.', 'n_nodes', '(', ')', '# number of exogenous states', 'n_mv', '=', 'dprocess', '.', 'n_inodes', '(', '0', ')', '# this assume number of integration nodes is constant', 'x0', '=', 'model', '.', 'calibration', '[', "'controls'", ']', 'v0', '=', 'model', '.', 'calibration', '[', "'values'", ']', 'parms', '=', 'model', '.', 'calibration', '[', "'parameters'", ']', 'n_x', '=', 'len', '(', 'x0', ')', 'n_v', '=', 'len', '(', 'v0', ')', 'n_s', '=', 'len', '(', 'model', '.', 'symbols', '[', "'states'", ']', ')', 'endo_grid', '=', 'model', '.', 'get_grid', '(', '*', '*', 'grid', ')', 'exo_grid', '=', 'dprocess', '.', 'grid', 'if', 'initial_guess', 'is', 'not', 'None', ':', 'mdrv', '=', 'initial_guess', 'else', ':', 'mdrv', '=', 'DecisionRule', '(', 'exo_grid', ',', 'endo_grid', ',', 'interp_type', '=', 'interp_type', ')', 'grid', '=', 'mdrv', '.', 'endo_grid', '.', 'nodes', '(', ')', 'N', '=', 'grid', '.', 'shape', '[', '0', ']', 'if', 'isinstance', '(', 'mdr', ',', 'np', '.', 'ndarray', ')', ':', 'controls', '=', 'mdr', 'else', ':', 'controls', '=', 'np', '.', 'zeros', '(', '(', 'n_ms', ',', 'N', ',', 'n_x', ')', ')', 'for', 'i_m', 'in', 'range', '(', 'n_ms', ')', ':', 'controls', '[', 'i_m', ',', ':', ',', ':', ']', '=', 'mdr', '.', 'eval_is', '(', 'i_m', ',', 'grid', ')', 'values_0', '=', 'np', '.', 'zeros', '(', '(', 'n_ms', ',', 'N', ',', 'n_v', ')', ')', 'if', 'initial_guess', 'is', 'None', ':', 'for', 'i_m', 'in', 'range', '(', 'n_ms', ')', ':', 'values_0', '[', 'i_m', ',', ':', ',', ':', ']', '=', 'v0', '[', 'None', ',', ':', ']', 'else', ':', 'for', 'i_m', 'in', 'range', '(', 'n_ms', ')', ':', 'values_0', '[', 'i_m', ',', ':', ',', ':', ']', '=', 'initial_guess', '.', 'eval_is', '(', 'i_m', ',', 'grid', ')', 'val', '=', 'model', '.', 'functions', '[', "'value'", ']', 'g', '=', 'model', '.', 'functions', '[', "'transition'", ']', 'sh_v', '=', 'values_0', '.', 'shape', 'err', '=', '10', 'inner_maxit', '=', '50', 'it', '=', '0', 'if', 'verbose', ':', 'headline', '=', "'|{0:^4} | {1:10} | {2:8} | {3:8} |'", '.', 'format', '(', "'N'", ',', "' Error'", ',', "'Gain'", ',', "'Time'", ')', 'stars', '=', "'-'", '*', 'len', '(', 'headline', ')', 'print', '(', 'stars', ')', 'print', '(', 'headline', ')', 'print', '(', 'stars', ')', 't1', '=', 'time', '.', 'time', '(', ')', 'err_0', '=', 'np', '.', 'nan', 'verbit', '=', '(', 'verbose', '==', "'full'", ')', 'while', 'err', '>', 'tol', 'and', 'it', '<', 'maxit', ':', 'it', '+=', '1', 't_start', '=', 'time', '.', 'time', '(', ')', 'mdrv', '.', 'set_values', '(', 'values_0', '.', 'reshape', '(', 'sh_v', ')', ')', 'values', '=', 'update_value', '(', 'val', ',', 'g', ',', 'grid', ',', 'controls', ',', 'values_0', ',', 'mdr', ',', 'mdrv', ',', 'dprocess', ',', 'parms', ')', '.', 'reshape', '(', '(', '-', '1', ',', 'n_v', ')', ')', 'err', '=', 'abs', '(', 'values', '.', 'reshape', '(', 'sh_v', ')', '-', 'values_0', ')', '.', 'max', '(', ')', 'err_SA', '=', 'err', '/', 'err_0', 'err_0', '=', 'err', 'values_0', '=', 'values', '.', 'reshape', '(', 'sh_v', ')', 't_finish', '=', 'time', '.', 'time', '(', ')', 'elapsed', '=', 't_finish', '-', 't_start', 'if', 'verbose', ':', 'print', '(', "'|{0:4} | {1:10.3e} | {2:8.3f} | {3:8.3f} |'", '.', 'format', '(', 'it', ',', 'err', ',', 'err_SA', ',', 'elapsed', ')', ')', '# values_0 = values.reshape(sh_v)', 't2', '=', 'time', '.', 'time', '(', ')', 'if', 'verbose', ':', 'print', '(', 'stars', ')', 'print', '(', '"Elapsed: {} seconds."', '.', 'format', '(', 't2', '-', 't1', ')', ')', 'print', '(', 'stars', ')', 'if', 'not', 'details', ':', 'return', 'mdrv', 'else', ':', 'return', 'EvaluationResult', '(', 'mdrv', ',', 'it', ',', 'tol', ',', 'err', ')'] | Compute value function corresponding to policy ``dr``
Parameters:
-----------
model:
"dtcscc" model. Must contain a 'value' function.
mdr:
decision rule to evaluate
Returns:
--------
decision rule:
value function (a function of the space similar to a decision rule
object) | ['Compute', 'value', 'function', 'corresponding', 'to', 'policy', 'dr'] | train | https://github.com/EconForge/dolo/blob/d91ddf148b009bf79852d9aec70f3a1877e0f79a/dolo/algos/value_iteration.py#L210-L339 |
6,242 | neovim/pynvim | pynvim/api/nvim.py | Nvim.async_call | def async_call(self, fn, *args, **kwargs):
"""Schedule `fn` to be called by the event loop soon.
This function is thread-safe, and is the only way code not
on the main thread could interact with nvim api objects.
This function can also be called in a synchronous
event handler, just before it returns, to defer execution
that shouldn't block neovim.
"""
call_point = ''.join(format_stack(None, 5)[:-1])
def handler():
try:
fn(*args, **kwargs)
except Exception as err:
msg = ("error caught while executing async callback:\n"
"{!r}\n{}\n \nthe call was requested at\n{}"
.format(err, format_exc_skip(1), call_point))
self._err_cb(msg)
raise
self._session.threadsafe_call(handler) | python | def async_call(self, fn, *args, **kwargs):
"""Schedule `fn` to be called by the event loop soon.
This function is thread-safe, and is the only way code not
on the main thread could interact with nvim api objects.
This function can also be called in a synchronous
event handler, just before it returns, to defer execution
that shouldn't block neovim.
"""
call_point = ''.join(format_stack(None, 5)[:-1])
def handler():
try:
fn(*args, **kwargs)
except Exception as err:
msg = ("error caught while executing async callback:\n"
"{!r}\n{}\n \nthe call was requested at\n{}"
.format(err, format_exc_skip(1), call_point))
self._err_cb(msg)
raise
self._session.threadsafe_call(handler) | ['def', 'async_call', '(', 'self', ',', 'fn', ',', '*', 'args', ',', '*', '*', 'kwargs', ')', ':', 'call_point', '=', "''", '.', 'join', '(', 'format_stack', '(', 'None', ',', '5', ')', '[', ':', '-', '1', ']', ')', 'def', 'handler', '(', ')', ':', 'try', ':', 'fn', '(', '*', 'args', ',', '*', '*', 'kwargs', ')', 'except', 'Exception', 'as', 'err', ':', 'msg', '=', '(', '"error caught while executing async callback:\\n"', '"{!r}\\n{}\\n \\nthe call was requested at\\n{}"', '.', 'format', '(', 'err', ',', 'format_exc_skip', '(', '1', ')', ',', 'call_point', ')', ')', 'self', '.', '_err_cb', '(', 'msg', ')', 'raise', 'self', '.', '_session', '.', 'threadsafe_call', '(', 'handler', ')'] | Schedule `fn` to be called by the event loop soon.
This function is thread-safe, and is the only way code not
on the main thread could interact with nvim api objects.
This function can also be called in a synchronous
event handler, just before it returns, to defer execution
that shouldn't block neovim. | ['Schedule', 'fn', 'to', 'be', 'called', 'by', 'the', 'event', 'loop', 'soon', '.'] | train | https://github.com/neovim/pynvim/blob/5e577188e6d7133f597ad0ce60dc6a4b1314064a/pynvim/api/nvim.py#L433-L454 |
6,243 | mass-project/mass_api_client | mass_api_client/resources/sample.py | DomainSample.create | def create(cls, domain, tlp_level=0, tags=[]):
"""
Create a new :class:`DomainSample` on the server.
:param domain: The domain as a string.
:param tlp_level: The TLP-Level
:param tags: Tags to add to the sample.
:return: The created sample.
"""
return cls._create(domain=domain, tlp_level=tlp_level, tags=tags) | python | def create(cls, domain, tlp_level=0, tags=[]):
"""
Create a new :class:`DomainSample` on the server.
:param domain: The domain as a string.
:param tlp_level: The TLP-Level
:param tags: Tags to add to the sample.
:return: The created sample.
"""
return cls._create(domain=domain, tlp_level=tlp_level, tags=tags) | ['def', 'create', '(', 'cls', ',', 'domain', ',', 'tlp_level', '=', '0', ',', 'tags', '=', '[', ']', ')', ':', 'return', 'cls', '.', '_create', '(', 'domain', '=', 'domain', ',', 'tlp_level', '=', 'tlp_level', ',', 'tags', '=', 'tags', ')'] | Create a new :class:`DomainSample` on the server.
:param domain: The domain as a string.
:param tlp_level: The TLP-Level
:param tags: Tags to add to the sample.
:return: The created sample. | ['Create', 'a', 'new', ':', 'class', ':', 'DomainSample', 'on', 'the', 'server', '.'] | train | https://github.com/mass-project/mass_api_client/blob/b200c32c93608bf3b2707fbf0e83a2228702e2c8/mass_api_client/resources/sample.py#L68-L77 |
6,244 | MacHu-GWU/crawlib-project | crawlib/pipeline/mongodb/query_builder.py | unfinished | def unfinished(finished_status,
update_interval,
status_key,
edit_at_key):
"""
Create dict query for pymongo that getting all unfinished task.
:param finished_status: int, status code that less than this
will be considered as unfinished.
:param update_interval: int, the record will be updated every x seconds.
:param status_key: status code field key, support dot notation.
:param edit_at_key: edit_at time field key, support dot notation.
:return: dict, a pymongo filter.
**中文文档**
状态码小于某个值, 或者, 现在距离更新时间已经超过一定阈值.
"""
return {
"$or": [
{status_key: {"$lt": finished_status}},
{edit_at_key: {"$lt": x_seconds_before_now(update_interval)}},
]
} | python | def unfinished(finished_status,
update_interval,
status_key,
edit_at_key):
"""
Create dict query for pymongo that getting all unfinished task.
:param finished_status: int, status code that less than this
will be considered as unfinished.
:param update_interval: int, the record will be updated every x seconds.
:param status_key: status code field key, support dot notation.
:param edit_at_key: edit_at time field key, support dot notation.
:return: dict, a pymongo filter.
**中文文档**
状态码小于某个值, 或者, 现在距离更新时间已经超过一定阈值.
"""
return {
"$or": [
{status_key: {"$lt": finished_status}},
{edit_at_key: {"$lt": x_seconds_before_now(update_interval)}},
]
} | ['def', 'unfinished', '(', 'finished_status', ',', 'update_interval', ',', 'status_key', ',', 'edit_at_key', ')', ':', 'return', '{', '"$or"', ':', '[', '{', 'status_key', ':', '{', '"$lt"', ':', 'finished_status', '}', '}', ',', '{', 'edit_at_key', ':', '{', '"$lt"', ':', 'x_seconds_before_now', '(', 'update_interval', ')', '}', '}', ',', ']', '}'] | Create dict query for pymongo that getting all unfinished task.
:param finished_status: int, status code that less than this
will be considered as unfinished.
:param update_interval: int, the record will be updated every x seconds.
:param status_key: status code field key, support dot notation.
:param edit_at_key: edit_at time field key, support dot notation.
:return: dict, a pymongo filter.
**中文文档**
状态码小于某个值, 或者, 现在距离更新时间已经超过一定阈值. | ['Create', 'dict', 'query', 'for', 'pymongo', 'that', 'getting', 'all', 'unfinished', 'task', '.'] | train | https://github.com/MacHu-GWU/crawlib-project/blob/241516f2a7a0a32c692f7af35a1f44064e8ce1ab/crawlib/pipeline/mongodb/query_builder.py#L52-L77 |
6,245 | saltstack/salt | salt/runners/queue.py | insert_runner | def insert_runner(fun, args=None, kwargs=None, queue=None, backend=None):
'''
Insert a reference to a runner into the queue so that it can be run later.
fun
The runner function that is going to be run
args
list or comma-seperated string of args to send to fun
kwargs
dictionary of keyword arguments to send to fun
queue
queue to insert the runner reference into
backend
backend that to use for the queue
CLI Example:
.. code-block:: bash
salt-run queue.insert_runner test.stdout_print
salt-run queue.insert_runner event.send test_insert_runner kwargs='{"data": {"foo": "bar"}}'
'''
if args is None:
args = []
elif isinstance(args, six.string_types):
args = args.split(',')
if kwargs is None:
kwargs = {}
queue_kwargs = __get_queue_opts(queue=queue, backend=backend)
data = {'fun': fun, 'args': args, 'kwargs': kwargs}
return insert(items=data, **queue_kwargs) | python | def insert_runner(fun, args=None, kwargs=None, queue=None, backend=None):
'''
Insert a reference to a runner into the queue so that it can be run later.
fun
The runner function that is going to be run
args
list or comma-seperated string of args to send to fun
kwargs
dictionary of keyword arguments to send to fun
queue
queue to insert the runner reference into
backend
backend that to use for the queue
CLI Example:
.. code-block:: bash
salt-run queue.insert_runner test.stdout_print
salt-run queue.insert_runner event.send test_insert_runner kwargs='{"data": {"foo": "bar"}}'
'''
if args is None:
args = []
elif isinstance(args, six.string_types):
args = args.split(',')
if kwargs is None:
kwargs = {}
queue_kwargs = __get_queue_opts(queue=queue, backend=backend)
data = {'fun': fun, 'args': args, 'kwargs': kwargs}
return insert(items=data, **queue_kwargs) | ['def', 'insert_runner', '(', 'fun', ',', 'args', '=', 'None', ',', 'kwargs', '=', 'None', ',', 'queue', '=', 'None', ',', 'backend', '=', 'None', ')', ':', 'if', 'args', 'is', 'None', ':', 'args', '=', '[', ']', 'elif', 'isinstance', '(', 'args', ',', 'six', '.', 'string_types', ')', ':', 'args', '=', 'args', '.', 'split', '(', "','", ')', 'if', 'kwargs', 'is', 'None', ':', 'kwargs', '=', '{', '}', 'queue_kwargs', '=', '__get_queue_opts', '(', 'queue', '=', 'queue', ',', 'backend', '=', 'backend', ')', 'data', '=', '{', "'fun'", ':', 'fun', ',', "'args'", ':', 'args', ',', "'kwargs'", ':', 'kwargs', '}', 'return', 'insert', '(', 'items', '=', 'data', ',', '*', '*', 'queue_kwargs', ')'] | Insert a reference to a runner into the queue so that it can be run later.
fun
The runner function that is going to be run
args
list or comma-seperated string of args to send to fun
kwargs
dictionary of keyword arguments to send to fun
queue
queue to insert the runner reference into
backend
backend that to use for the queue
CLI Example:
.. code-block:: bash
salt-run queue.insert_runner test.stdout_print
salt-run queue.insert_runner event.send test_insert_runner kwargs='{"data": {"foo": "bar"}}' | ['Insert', 'a', 'reference', 'to', 'a', 'runner', 'into', 'the', 'queue', 'so', 'that', 'it', 'can', 'be', 'run', 'later', '.'] | train | https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/runners/queue.py#L242-L277 |
6,246 | brianhie/scanorama | bin/unsupervised.py | silhouette_score | def silhouette_score(X, labels, metric='euclidean', sample_size=None,
random_state=None, **kwds):
"""Compute the mean Silhouette Coefficient of all samples.
The Silhouette Coefficient is calculated using the mean intra-cluster
distance (``a``) and the mean nearest-cluster distance (``b``) for each
sample. The Silhouette Coefficient for a sample is ``(b - a) / max(a,
b)``. To clarify, ``b`` is the distance between a sample and the nearest
cluster that the sample is not a part of.
Note that Silhouette Coefficient is only defined if number of labels
is 2 <= n_labels <= n_samples - 1.
This function returns the mean Silhouette Coefficient over all samples.
To obtain the values for each sample, use :func:`silhouette_samples`.
The best value is 1 and the worst value is -1. Values near 0 indicate
overlapping clusters. Negative values generally indicate that a sample has
been assigned to the wrong cluster, as a different cluster is more similar.
Read more in the :ref:`User Guide <silhouette_coefficient>`.
Parameters
----------
X : array [n_samples_a, n_samples_a] if metric == "precomputed", or, \
[n_samples_a, n_features] otherwise
Array of pairwise distances between samples, or a feature array.
labels : array, shape = [n_samples]
Predicted labels for each sample.
metric : string, or callable
The metric to use when calculating distance between instances in a
feature array. If metric is a string, it must be one of the options
allowed by :func:`metrics.pairwise.pairwise_distances
<sklearn.metrics.pairwise.pairwise_distances>`. If X is the distance
array itself, use ``metric="precomputed"``.
sample_size : int or None
The size of the sample to use when computing the Silhouette Coefficient
on a random subset of the data.
If ``sample_size is None``, no sampling is used.
random_state : int, RandomState instance or None, optional (default=None)
The generator used to randomly select a subset of samples. If int,
random_state is the seed used by the random number generator; If
RandomState instance, random_state is the random number generator; If
None, the random number generator is the RandomState instance used by
`np.random`. Used when ``sample_size is not None``.
**kwds : optional keyword parameters
Any further parameters are passed directly to the distance function.
If using a scipy.spatial.distance metric, the parameters are still
metric dependent. See the scipy docs for usage examples.
Returns
-------
silhouette : float
Mean Silhouette Coefficient for all samples.
References
----------
.. [1] `Peter J. Rousseeuw (1987). "Silhouettes: a Graphical Aid to the
Interpretation and Validation of Cluster Analysis". Computational
and Applied Mathematics 20: 53-65.
<http://www.sciencedirect.com/science/article/pii/0377042787901257>`_
.. [2] `Wikipedia entry on the Silhouette Coefficient
<https://en.wikipedia.org/wiki/Silhouette_(clustering)>`_
"""
if sample_size is not None:
X, labels = check_X_y(X, labels, accept_sparse=['csc', 'csr'])
random_state = check_random_state(random_state)
indices = random_state.permutation(X.shape[0])[:sample_size]
if metric == "precomputed":
X, labels = X[indices].T[indices].T, labels[indices]
else:
X, labels = X[indices], labels[indices]
return np.mean(silhouette_samples(X, labels, metric=metric, **kwds)) | python | def silhouette_score(X, labels, metric='euclidean', sample_size=None,
random_state=None, **kwds):
"""Compute the mean Silhouette Coefficient of all samples.
The Silhouette Coefficient is calculated using the mean intra-cluster
distance (``a``) and the mean nearest-cluster distance (``b``) for each
sample. The Silhouette Coefficient for a sample is ``(b - a) / max(a,
b)``. To clarify, ``b`` is the distance between a sample and the nearest
cluster that the sample is not a part of.
Note that Silhouette Coefficient is only defined if number of labels
is 2 <= n_labels <= n_samples - 1.
This function returns the mean Silhouette Coefficient over all samples.
To obtain the values for each sample, use :func:`silhouette_samples`.
The best value is 1 and the worst value is -1. Values near 0 indicate
overlapping clusters. Negative values generally indicate that a sample has
been assigned to the wrong cluster, as a different cluster is more similar.
Read more in the :ref:`User Guide <silhouette_coefficient>`.
Parameters
----------
X : array [n_samples_a, n_samples_a] if metric == "precomputed", or, \
[n_samples_a, n_features] otherwise
Array of pairwise distances between samples, or a feature array.
labels : array, shape = [n_samples]
Predicted labels for each sample.
metric : string, or callable
The metric to use when calculating distance between instances in a
feature array. If metric is a string, it must be one of the options
allowed by :func:`metrics.pairwise.pairwise_distances
<sklearn.metrics.pairwise.pairwise_distances>`. If X is the distance
array itself, use ``metric="precomputed"``.
sample_size : int or None
The size of the sample to use when computing the Silhouette Coefficient
on a random subset of the data.
If ``sample_size is None``, no sampling is used.
random_state : int, RandomState instance or None, optional (default=None)
The generator used to randomly select a subset of samples. If int,
random_state is the seed used by the random number generator; If
RandomState instance, random_state is the random number generator; If
None, the random number generator is the RandomState instance used by
`np.random`. Used when ``sample_size is not None``.
**kwds : optional keyword parameters
Any further parameters are passed directly to the distance function.
If using a scipy.spatial.distance metric, the parameters are still
metric dependent. See the scipy docs for usage examples.
Returns
-------
silhouette : float
Mean Silhouette Coefficient for all samples.
References
----------
.. [1] `Peter J. Rousseeuw (1987). "Silhouettes: a Graphical Aid to the
Interpretation and Validation of Cluster Analysis". Computational
and Applied Mathematics 20: 53-65.
<http://www.sciencedirect.com/science/article/pii/0377042787901257>`_
.. [2] `Wikipedia entry on the Silhouette Coefficient
<https://en.wikipedia.org/wiki/Silhouette_(clustering)>`_
"""
if sample_size is not None:
X, labels = check_X_y(X, labels, accept_sparse=['csc', 'csr'])
random_state = check_random_state(random_state)
indices = random_state.permutation(X.shape[0])[:sample_size]
if metric == "precomputed":
X, labels = X[indices].T[indices].T, labels[indices]
else:
X, labels = X[indices], labels[indices]
return np.mean(silhouette_samples(X, labels, metric=metric, **kwds)) | ['def', 'silhouette_score', '(', 'X', ',', 'labels', ',', 'metric', '=', "'euclidean'", ',', 'sample_size', '=', 'None', ',', 'random_state', '=', 'None', ',', '*', '*', 'kwds', ')', ':', 'if', 'sample_size', 'is', 'not', 'None', ':', 'X', ',', 'labels', '=', 'check_X_y', '(', 'X', ',', 'labels', ',', 'accept_sparse', '=', '[', "'csc'", ',', "'csr'", ']', ')', 'random_state', '=', 'check_random_state', '(', 'random_state', ')', 'indices', '=', 'random_state', '.', 'permutation', '(', 'X', '.', 'shape', '[', '0', ']', ')', '[', ':', 'sample_size', ']', 'if', 'metric', '==', '"precomputed"', ':', 'X', ',', 'labels', '=', 'X', '[', 'indices', ']', '.', 'T', '[', 'indices', ']', '.', 'T', ',', 'labels', '[', 'indices', ']', 'else', ':', 'X', ',', 'labels', '=', 'X', '[', 'indices', ']', ',', 'labels', '[', 'indices', ']', 'return', 'np', '.', 'mean', '(', 'silhouette_samples', '(', 'X', ',', 'labels', ',', 'metric', '=', 'metric', ',', '*', '*', 'kwds', ')', ')'] | Compute the mean Silhouette Coefficient of all samples.
The Silhouette Coefficient is calculated using the mean intra-cluster
distance (``a``) and the mean nearest-cluster distance (``b``) for each
sample. The Silhouette Coefficient for a sample is ``(b - a) / max(a,
b)``. To clarify, ``b`` is the distance between a sample and the nearest
cluster that the sample is not a part of.
Note that Silhouette Coefficient is only defined if number of labels
is 2 <= n_labels <= n_samples - 1.
This function returns the mean Silhouette Coefficient over all samples.
To obtain the values for each sample, use :func:`silhouette_samples`.
The best value is 1 and the worst value is -1. Values near 0 indicate
overlapping clusters. Negative values generally indicate that a sample has
been assigned to the wrong cluster, as a different cluster is more similar.
Read more in the :ref:`User Guide <silhouette_coefficient>`.
Parameters
----------
X : array [n_samples_a, n_samples_a] if metric == "precomputed", or, \
[n_samples_a, n_features] otherwise
Array of pairwise distances between samples, or a feature array.
labels : array, shape = [n_samples]
Predicted labels for each sample.
metric : string, or callable
The metric to use when calculating distance between instances in a
feature array. If metric is a string, it must be one of the options
allowed by :func:`metrics.pairwise.pairwise_distances
<sklearn.metrics.pairwise.pairwise_distances>`. If X is the distance
array itself, use ``metric="precomputed"``.
sample_size : int or None
The size of the sample to use when computing the Silhouette Coefficient
on a random subset of the data.
If ``sample_size is None``, no sampling is used.
random_state : int, RandomState instance or None, optional (default=None)
The generator used to randomly select a subset of samples. If int,
random_state is the seed used by the random number generator; If
RandomState instance, random_state is the random number generator; If
None, the random number generator is the RandomState instance used by
`np.random`. Used when ``sample_size is not None``.
**kwds : optional keyword parameters
Any further parameters are passed directly to the distance function.
If using a scipy.spatial.distance metric, the parameters are still
metric dependent. See the scipy docs for usage examples.
Returns
-------
silhouette : float
Mean Silhouette Coefficient for all samples.
References
----------
.. [1] `Peter J. Rousseeuw (1987). "Silhouettes: a Graphical Aid to the
Interpretation and Validation of Cluster Analysis". Computational
and Applied Mathematics 20: 53-65.
<http://www.sciencedirect.com/science/article/pii/0377042787901257>`_
.. [2] `Wikipedia entry on the Silhouette Coefficient
<https://en.wikipedia.org/wiki/Silhouette_(clustering)>`_ | ['Compute', 'the', 'mean', 'Silhouette', 'Coefficient', 'of', 'all', 'samples', '.'] | train | https://github.com/brianhie/scanorama/blob/57aafac87d07a8d682f57450165dd07f066ebb3c/bin/unsupervised.py#L27-L106 |
6,247 | buildbot/buildbot | master/buildbot/reporters/gerrit.py | GerritStatusPush._gerritCmd | def _gerritCmd(self, *args):
'''Construct a command as a list of strings suitable for
:func:`subprocess.call`.
'''
if self.gerrit_identity_file is not None:
options = ['-i', self.gerrit_identity_file]
else:
options = []
return ['ssh'] + options + [
'@'.join((self.gerrit_username, self.gerrit_server)),
'-p', str(self.gerrit_port),
'gerrit'
] + list(args) | python | def _gerritCmd(self, *args):
'''Construct a command as a list of strings suitable for
:func:`subprocess.call`.
'''
if self.gerrit_identity_file is not None:
options = ['-i', self.gerrit_identity_file]
else:
options = []
return ['ssh'] + options + [
'@'.join((self.gerrit_username, self.gerrit_server)),
'-p', str(self.gerrit_port),
'gerrit'
] + list(args) | ['def', '_gerritCmd', '(', 'self', ',', '*', 'args', ')', ':', 'if', 'self', '.', 'gerrit_identity_file', 'is', 'not', 'None', ':', 'options', '=', '[', "'-i'", ',', 'self', '.', 'gerrit_identity_file', ']', 'else', ':', 'options', '=', '[', ']', 'return', '[', "'ssh'", ']', '+', 'options', '+', '[', "'@'", '.', 'join', '(', '(', 'self', '.', 'gerrit_username', ',', 'self', '.', 'gerrit_server', ')', ')', ',', "'-p'", ',', 'str', '(', 'self', '.', 'gerrit_port', ')', ',', "'gerrit'", ']', '+', 'list', '(', 'args', ')'] | Construct a command as a list of strings suitable for
:func:`subprocess.call`. | ['Construct', 'a', 'command', 'as', 'a', 'list', 'of', 'strings', 'suitable', 'for', ':', 'func', ':', 'subprocess', '.', 'call', '.'] | train | https://github.com/buildbot/buildbot/blob/5df3cfae6d760557d99156633c32b1822a1e130c/master/buildbot/reporters/gerrit.py#L185-L197 |
6,248 | JnyJny/Geometry | Geometry/point.py | Point.cross | def cross(self, other):
'''
:other: Point or point equivalent
:return: float
Vector cross product of points U (self) and V (other), computed:
U x V = (u1*i + u2*j + u3*k) x (v1*i + v2*j + v3*k)
s1 = u2v3 - u3v2
s2 = u3v1 - u1v3
s3 = u1v2 - u2v1
U x V = s1 + s2 + s3
Returns a float.
'''
b = self.__class__._convert(other)
return sum([(self.y * b.z) - (self.z * b.y),
(self.z * b.x) - (self.x * b.z),
(self.x * b.y) - (self.y * b.x)]) | python | def cross(self, other):
'''
:other: Point or point equivalent
:return: float
Vector cross product of points U (self) and V (other), computed:
U x V = (u1*i + u2*j + u3*k) x (v1*i + v2*j + v3*k)
s1 = u2v3 - u3v2
s2 = u3v1 - u1v3
s3 = u1v2 - u2v1
U x V = s1 + s2 + s3
Returns a float.
'''
b = self.__class__._convert(other)
return sum([(self.y * b.z) - (self.z * b.y),
(self.z * b.x) - (self.x * b.z),
(self.x * b.y) - (self.y * b.x)]) | ['def', 'cross', '(', 'self', ',', 'other', ')', ':', 'b', '=', 'self', '.', '__class__', '.', '_convert', '(', 'other', ')', 'return', 'sum', '(', '[', '(', 'self', '.', 'y', '*', 'b', '.', 'z', ')', '-', '(', 'self', '.', 'z', '*', 'b', '.', 'y', ')', ',', '(', 'self', '.', 'z', '*', 'b', '.', 'x', ')', '-', '(', 'self', '.', 'x', '*', 'b', '.', 'z', ')', ',', '(', 'self', '.', 'x', '*', 'b', '.', 'y', ')', '-', '(', 'self', '.', 'y', '*', 'b', '.', 'x', ')', ']', ')'] | :other: Point or point equivalent
:return: float
Vector cross product of points U (self) and V (other), computed:
U x V = (u1*i + u2*j + u3*k) x (v1*i + v2*j + v3*k)
s1 = u2v3 - u3v2
s2 = u3v1 - u1v3
s3 = u1v2 - u2v1
U x V = s1 + s2 + s3
Returns a float. | [':', 'other', ':', 'Point', 'or', 'point', 'equivalent', ':', 'return', ':', 'float'] | train | https://github.com/JnyJny/Geometry/blob/3500f815fa56c535b36d1b6fd0afe69ce5d055be/Geometry/point.py#L1260-L1281 |
6,249 | bamthomas/aioimaplib | aioimaplib/aioimaplib.py | quoted | def quoted(arg):
""" Given a string, return a quoted string as per RFC 3501, section 9.
Implementation copied from https://github.com/mjs/imapclient
(imapclient/imapclient.py), 3-clause BSD license
"""
if isinstance(arg, str):
arg = arg.replace('\\', '\\\\')
arg = arg.replace('"', '\\"')
q = '"'
else:
arg = arg.replace(b'\\', b'\\\\')
arg = arg.replace(b'"', b'\\"')
q = b'"'
return q + arg + q | python | def quoted(arg):
""" Given a string, return a quoted string as per RFC 3501, section 9.
Implementation copied from https://github.com/mjs/imapclient
(imapclient/imapclient.py), 3-clause BSD license
"""
if isinstance(arg, str):
arg = arg.replace('\\', '\\\\')
arg = arg.replace('"', '\\"')
q = '"'
else:
arg = arg.replace(b'\\', b'\\\\')
arg = arg.replace(b'"', b'\\"')
q = b'"'
return q + arg + q | ['def', 'quoted', '(', 'arg', ')', ':', 'if', 'isinstance', '(', 'arg', ',', 'str', ')', ':', 'arg', '=', 'arg', '.', 'replace', '(', "'\\\\'", ',', "'\\\\\\\\'", ')', 'arg', '=', 'arg', '.', 'replace', '(', '\'"\'', ',', '\'\\\\"\'', ')', 'q', '=', '\'"\'', 'else', ':', 'arg', '=', 'arg', '.', 'replace', '(', "b'\\\\'", ',', "b'\\\\\\\\'", ')', 'arg', '=', 'arg', '.', 'replace', '(', 'b\'"\'', ',', 'b\'\\\\"\'', ')', 'q', '=', 'b\'"\'', 'return', 'q', '+', 'arg', '+', 'q'] | Given a string, return a quoted string as per RFC 3501, section 9.
Implementation copied from https://github.com/mjs/imapclient
(imapclient/imapclient.py), 3-clause BSD license | ['Given', 'a', 'string', 'return', 'a', 'quoted', 'string', 'as', 'per', 'RFC', '3501', 'section', '9', '.'] | train | https://github.com/bamthomas/aioimaplib/blob/9670d43950cafc4d41aab7a36824b8051fa89899/aioimaplib/aioimaplib.py#L100-L114 |
6,250 | ipazc/mtcnn | mtcnn/layer_factory.py | LayerFactory.new_conv | def new_conv(self, name: str, kernel_size: tuple, channels_output: int,
stride_size: tuple, padding: str='SAME',
group: int=1, biased: bool=True, relu: bool=True, input_layer_name: str=None):
"""
Creates a convolution layer for the network.
:param name: name for the layer
:param kernel_size: tuple containing the size of the kernel (Width, Height)
:param channels_output: ¿? Perhaps number of channels in the output? it is used as the bias size.
:param stride_size: tuple containing the size of the stride (Width, Height)
:param padding: Type of padding. Available values are: ('SAME', 'VALID')
:param group: groups for the kernel operation. More info required.
:param biased: boolean flag to set if biased or not.
:param relu: boolean flag to set if ReLu should be applied at the end of the layer or not.
:param input_layer_name: name of the input layer for this layer. If None, it will take the last added layer of
the network.
"""
# Verify that the padding is acceptable
self.__validate_padding(padding)
input_layer = self.__network.get_layer(input_layer_name)
# Get the number of channels in the input
channels_input = int(input_layer.get_shape()[-1])
# Verify that the grouping parameter is valid
self.__validate_grouping(channels_input, channels_output, group)
# Convolution for a given input and kernel
convolve = lambda input_val, kernel: tf.nn.conv2d(input_val, kernel, [1, stride_size[1], stride_size[0], 1],
padding=padding)
with tf.variable_scope(name) as scope:
kernel = self.__make_var('weights', shape=[kernel_size[1], kernel_size[0], channels_input // group, channels_output])
output = convolve(input_layer, kernel)
# Add the biases, if required
if biased:
biases = self.__make_var('biases', [channels_output])
output = tf.nn.bias_add(output, biases)
# Apply ReLU non-linearity, if required
if relu:
output = tf.nn.relu(output, name=scope.name)
self.__network.add_layer(name, layer_output=output) | python | def new_conv(self, name: str, kernel_size: tuple, channels_output: int,
stride_size: tuple, padding: str='SAME',
group: int=1, biased: bool=True, relu: bool=True, input_layer_name: str=None):
"""
Creates a convolution layer for the network.
:param name: name for the layer
:param kernel_size: tuple containing the size of the kernel (Width, Height)
:param channels_output: ¿? Perhaps number of channels in the output? it is used as the bias size.
:param stride_size: tuple containing the size of the stride (Width, Height)
:param padding: Type of padding. Available values are: ('SAME', 'VALID')
:param group: groups for the kernel operation. More info required.
:param biased: boolean flag to set if biased or not.
:param relu: boolean flag to set if ReLu should be applied at the end of the layer or not.
:param input_layer_name: name of the input layer for this layer. If None, it will take the last added layer of
the network.
"""
# Verify that the padding is acceptable
self.__validate_padding(padding)
input_layer = self.__network.get_layer(input_layer_name)
# Get the number of channels in the input
channels_input = int(input_layer.get_shape()[-1])
# Verify that the grouping parameter is valid
self.__validate_grouping(channels_input, channels_output, group)
# Convolution for a given input and kernel
convolve = lambda input_val, kernel: tf.nn.conv2d(input_val, kernel, [1, stride_size[1], stride_size[0], 1],
padding=padding)
with tf.variable_scope(name) as scope:
kernel = self.__make_var('weights', shape=[kernel_size[1], kernel_size[0], channels_input // group, channels_output])
output = convolve(input_layer, kernel)
# Add the biases, if required
if biased:
biases = self.__make_var('biases', [channels_output])
output = tf.nn.bias_add(output, biases)
# Apply ReLU non-linearity, if required
if relu:
output = tf.nn.relu(output, name=scope.name)
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:param name: name for the layer
:param kernel_size: tuple containing the size of the kernel (Width, Height)
:param channels_output: ¿? Perhaps number of channels in the output? it is used as the bias size.
:param stride_size: tuple containing the size of the stride (Width, Height)
:param padding: Type of padding. Available values are: ('SAME', 'VALID')
:param group: groups for the kernel operation. More info required.
:param biased: boolean flag to set if biased or not.
:param relu: boolean flag to set if ReLu should be applied at the end of the layer or not.
:param input_layer_name: name of the input layer for this layer. If None, it will take the last added layer of
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6,251 | BlueBrain/NeuroM | examples/section_ids.py | get_segment | def get_segment(neuron, section_id, segment_id):
'''Get a segment given a section and segment id
Returns:
array of two [x, y, z, r] points defining segment
'''
sec = neuron.sections[section_id]
return sec.points[segment_id:segment_id + 2][:, COLS.XYZR] | python | def get_segment(neuron, section_id, segment_id):
'''Get a segment given a section and segment id
Returns:
array of two [x, y, z, r] points defining segment
'''
sec = neuron.sections[section_id]
return sec.points[segment_id:segment_id + 2][:, COLS.XYZR] | ['def', 'get_segment', '(', 'neuron', ',', 'section_id', ',', 'segment_id', ')', ':', 'sec', '=', 'neuron', '.', 'sections', '[', 'section_id', ']', 'return', 'sec', '.', 'points', '[', 'segment_id', ':', 'segment_id', '+', '2', ']', '[', ':', ',', 'COLS', '.', 'XYZR', ']'] | Get a segment given a section and segment id
Returns:
array of two [x, y, z, r] points defining segment | ['Get', 'a', 'segment', 'given', 'a', 'section', 'and', 'segment', 'id'] | train | https://github.com/BlueBrain/NeuroM/blob/254bb73535b20053d175bc4725bade662177d12b/examples/section_ids.py#L37-L44 |
6,252 | kronenthaler/mod-pbxproj | pbxproj/pbxextensions/ProjectFlags.py | ProjectFlags.add_flags | def add_flags(self, flag_name, flags, target_name=None, configuration_name=None):
"""
Adds the given flags to the flag_name section of the target on the configurations
:param flag_name: name of the flag to be added the values to
:param flags: A string or array of strings
:param target_name: Target name or list of target names to add the flag to or None for every target
:param configuration_name: Configuration name to add the flag to or None for every configuration
:return: void
"""
for configuration in self.objects.get_configurations_on_targets(target_name, configuration_name):
configuration.add_flags(flag_name, flags) | python | def add_flags(self, flag_name, flags, target_name=None, configuration_name=None):
"""
Adds the given flags to the flag_name section of the target on the configurations
:param flag_name: name of the flag to be added the values to
:param flags: A string or array of strings
:param target_name: Target name or list of target names to add the flag to or None for every target
:param configuration_name: Configuration name to add the flag to or None for every configuration
:return: void
"""
for configuration in self.objects.get_configurations_on_targets(target_name, configuration_name):
configuration.add_flags(flag_name, flags) | ['def', 'add_flags', '(', 'self', ',', 'flag_name', ',', 'flags', ',', 'target_name', '=', 'None', ',', 'configuration_name', '=', 'None', ')', ':', 'for', 'configuration', 'in', 'self', '.', 'objects', '.', 'get_configurations_on_targets', '(', 'target_name', ',', 'configuration_name', ')', ':', 'configuration', '.', 'add_flags', '(', 'flag_name', ',', 'flags', ')'] | Adds the given flags to the flag_name section of the target on the configurations
:param flag_name: name of the flag to be added the values to
:param flags: A string or array of strings
:param target_name: Target name or list of target names to add the flag to or None for every target
:param configuration_name: Configuration name to add the flag to or None for every configuration
:return: void | ['Adds', 'the', 'given', 'flags', 'to', 'the', 'flag_name', 'section', 'of', 'the', 'target', 'on', 'the', 'configurations', ':', 'param', 'flag_name', ':', 'name', 'of', 'the', 'flag', 'to', 'be', 'added', 'the', 'values', 'to', ':', 'param', 'flags', ':', 'A', 'string', 'or', 'array', 'of', 'strings', ':', 'param', 'target_name', ':', 'Target', 'name', 'or', 'list', 'of', 'target', 'names', 'to', 'add', 'the', 'flag', 'to', 'or', 'None', 'for', 'every', 'target', ':', 'param', 'configuration_name', ':', 'Configuration', 'name', 'to', 'add', 'the', 'flag', 'to', 'or', 'None', 'for', 'every', 'configuration', ':', 'return', ':', 'void'] | train | https://github.com/kronenthaler/mod-pbxproj/blob/8de3cbdd3210480ddbb1fa0f50a4f4ea87de6e71/pbxproj/pbxextensions/ProjectFlags.py#L13-L23 |
6,253 | eleme/ruskit | ruskit/distribute.py | MaxFlowSolver.from_nodes | def from_nodes(cls, nodes, new_nodes, max_slaves_limit=None):
'''When this is used only for peeking reuslt
`new_nodes` can be any type with `host` and `port` attributes
'''
param = gen_distribution(nodes, new_nodes)
param['max_slaves_limit'] = max_slaves_limit
return cls(**param) | python | def from_nodes(cls, nodes, new_nodes, max_slaves_limit=None):
'''When this is used only for peeking reuslt
`new_nodes` can be any type with `host` and `port` attributes
'''
param = gen_distribution(nodes, new_nodes)
param['max_slaves_limit'] = max_slaves_limit
return cls(**param) | ['def', 'from_nodes', '(', 'cls', ',', 'nodes', ',', 'new_nodes', ',', 'max_slaves_limit', '=', 'None', ')', ':', 'param', '=', 'gen_distribution', '(', 'nodes', ',', 'new_nodes', ')', 'param', '[', "'max_slaves_limit'", ']', '=', 'max_slaves_limit', 'return', 'cls', '(', '*', '*', 'param', ')'] | When this is used only for peeking reuslt
`new_nodes` can be any type with `host` and `port` attributes | ['When', 'this', 'is', 'used', 'only', 'for', 'peeking', 'reuslt', 'new_nodes', 'can', 'be', 'any', 'type', 'with', 'host', 'and', 'port', 'attributes'] | train | https://github.com/eleme/ruskit/blob/2e8c5a3f6a65b8aeb07012b4e2c8ba324d887c3b/ruskit/distribute.py#L83-L89 |
6,254 | merll/docker-fabric | dockerfabric/apiclient.py | DockerFabricClient.close | def close(self):
"""
Closes the connection and any tunnels created for it.
"""
try:
super(DockerFabricClient, self).close()
finally:
if self._tunnel is not None:
self._tunnel.close() | python | def close(self):
"""
Closes the connection and any tunnels created for it.
"""
try:
super(DockerFabricClient, self).close()
finally:
if self._tunnel is not None:
self._tunnel.close() | ['def', 'close', '(', 'self', ')', ':', 'try', ':', 'super', '(', 'DockerFabricClient', ',', 'self', ')', '.', 'close', '(', ')', 'finally', ':', 'if', 'self', '.', '_tunnel', 'is', 'not', 'None', ':', 'self', '.', '_tunnel', '.', 'close', '(', ')'] | Closes the connection and any tunnels created for it. | ['Closes', 'the', 'connection', 'and', 'any', 'tunnels', 'created', 'for', 'it', '.'] | train | https://github.com/merll/docker-fabric/blob/785d84e40e17265b667d8b11a6e30d8e6b2bf8d4/dockerfabric/apiclient.py#L137-L145 |
6,255 | rwl/pylon | contrib/public/services/jsonrpc/__init__.py | SimpleServiceHandler.handleNotification | def handleNotification(self, req):
"""handles a notification request by calling the appropriete method the service exposes"""
name = req["method"]
params = req["params"]
try: #to get a callable obj
obj = getMethodByName(self.service, name)
rslt = obj(*params)
except:
pass | python | def handleNotification(self, req):
"""handles a notification request by calling the appropriete method the service exposes"""
name = req["method"]
params = req["params"]
try: #to get a callable obj
obj = getMethodByName(self.service, name)
rslt = obj(*params)
except:
pass | ['def', 'handleNotification', '(', 'self', ',', 'req', ')', ':', 'name', '=', 'req', '[', '"method"', ']', 'params', '=', 'req', '[', '"params"', ']', 'try', ':', '#to get a callable obj ', 'obj', '=', 'getMethodByName', '(', 'self', '.', 'service', ',', 'name', ')', 'rslt', '=', 'obj', '(', '*', 'params', ')', 'except', ':', 'pass'] | handles a notification request by calling the appropriete method the service exposes | ['handles', 'a', 'notification', 'request', 'by', 'calling', 'the', 'appropriete', 'method', 'the', 'service', 'exposes'] | train | https://github.com/rwl/pylon/blob/916514255db1ae1661406f0283df756baf960d14/contrib/public/services/jsonrpc/__init__.py#L229-L237 |
6,256 | ibis-project/ibis | ibis/expr/analytics.py | histogram | def histogram(
arg, nbins=None, binwidth=None, base=None, closed='left', aux_hash=None
):
"""
Compute a histogram with fixed width bins
Parameters
----------
arg : numeric array expression
nbins : int, default None
If supplied, will be used to compute the binwidth
binwidth : number, default None
If not supplied, computed from the data (actual max and min values)
base : number, default None
closed : {'left', 'right'}, default 'left'
Which side of each interval is closed
Returns
-------
histogrammed : coded value expression
"""
op = Histogram(
arg, nbins, binwidth, base, closed=closed, aux_hash=aux_hash
)
return op.to_expr() | python | def histogram(
arg, nbins=None, binwidth=None, base=None, closed='left', aux_hash=None
):
"""
Compute a histogram with fixed width bins
Parameters
----------
arg : numeric array expression
nbins : int, default None
If supplied, will be used to compute the binwidth
binwidth : number, default None
If not supplied, computed from the data (actual max and min values)
base : number, default None
closed : {'left', 'right'}, default 'left'
Which side of each interval is closed
Returns
-------
histogrammed : coded value expression
"""
op = Histogram(
arg, nbins, binwidth, base, closed=closed, aux_hash=aux_hash
)
return op.to_expr() | ['def', 'histogram', '(', 'arg', ',', 'nbins', '=', 'None', ',', 'binwidth', '=', 'None', ',', 'base', '=', 'None', ',', 'closed', '=', "'left'", ',', 'aux_hash', '=', 'None', ')', ':', 'op', '=', 'Histogram', '(', 'arg', ',', 'nbins', ',', 'binwidth', ',', 'base', ',', 'closed', '=', 'closed', ',', 'aux_hash', '=', 'aux_hash', ')', 'return', 'op', '.', 'to_expr', '(', ')'] | Compute a histogram with fixed width bins
Parameters
----------
arg : numeric array expression
nbins : int, default None
If supplied, will be used to compute the binwidth
binwidth : number, default None
If not supplied, computed from the data (actual max and min values)
base : number, default None
closed : {'left', 'right'}, default 'left'
Which side of each interval is closed
Returns
-------
histogrammed : coded value expression | ['Compute', 'a', 'histogram', 'with', 'fixed', 'width', 'bins'] | train | https://github.com/ibis-project/ibis/blob/1e39a5fd9ef088b45c155e8a5f541767ee8ef2e7/ibis/expr/analytics.py#L127-L151 |
6,257 | ssato/python-anytemplate | anytemplate/engines/base.py | fallback_render | def fallback_render(template, context, at_paths=None,
at_encoding=anytemplate.compat.ENCODING,
**kwargs):
"""
Render from given template and context.
This is a basic implementation actually does nothing and just returns
the content of given template file `template`.
:param template: Template file path
:param context: A dict or dict-like object to instantiate given
template file
:param at_paths: Template search paths
:param at_encoding: Template encoding
:param kwargs: Keyword arguments passed to the template engine to
render templates with specific features enabled.
:return: Rendered result string
"""
tmpl = anytemplate.utils.find_template_from_path(template, at_paths)
if tmpl is None:
raise TemplateNotFound("template: %s" % template)
try:
return anytemplate.compat.copen(tmpl, encoding=at_encoding).read()
except UnicodeDecodeError:
return open(tmpl).read() | python | def fallback_render(template, context, at_paths=None,
at_encoding=anytemplate.compat.ENCODING,
**kwargs):
"""
Render from given template and context.
This is a basic implementation actually does nothing and just returns
the content of given template file `template`.
:param template: Template file path
:param context: A dict or dict-like object to instantiate given
template file
:param at_paths: Template search paths
:param at_encoding: Template encoding
:param kwargs: Keyword arguments passed to the template engine to
render templates with specific features enabled.
:return: Rendered result string
"""
tmpl = anytemplate.utils.find_template_from_path(template, at_paths)
if tmpl is None:
raise TemplateNotFound("template: %s" % template)
try:
return anytemplate.compat.copen(tmpl, encoding=at_encoding).read()
except UnicodeDecodeError:
return open(tmpl).read() | ['def', 'fallback_render', '(', 'template', ',', 'context', ',', 'at_paths', '=', 'None', ',', 'at_encoding', '=', 'anytemplate', '.', 'compat', '.', 'ENCODING', ',', '*', '*', 'kwargs', ')', ':', 'tmpl', '=', 'anytemplate', '.', 'utils', '.', 'find_template_from_path', '(', 'template', ',', 'at_paths', ')', 'if', 'tmpl', 'is', 'None', ':', 'raise', 'TemplateNotFound', '(', '"template: %s"', '%', 'template', ')', 'try', ':', 'return', 'anytemplate', '.', 'compat', '.', 'copen', '(', 'tmpl', ',', 'encoding', '=', 'at_encoding', ')', '.', 'read', '(', ')', 'except', 'UnicodeDecodeError', ':', 'return', 'open', '(', 'tmpl', ')', '.', 'read', '(', ')'] | Render from given template and context.
This is a basic implementation actually does nothing and just returns
the content of given template file `template`.
:param template: Template file path
:param context: A dict or dict-like object to instantiate given
template file
:param at_paths: Template search paths
:param at_encoding: Template encoding
:param kwargs: Keyword arguments passed to the template engine to
render templates with specific features enabled.
:return: Rendered result string | ['Render', 'from', 'given', 'template', 'and', 'context', '.'] | train | https://github.com/ssato/python-anytemplate/blob/3e56baa914bd47f044083b20e33100f836443596/anytemplate/engines/base.py#L66-L92 |
6,258 | NASA-AMMOS/AIT-Core | ait/core/dtype.py | ArrayType._assertIndex | def _assertIndex(self, index):
"""Raise TypeError or IndexError if index is not an integer or out of
range for the number of elements in this array, respectively.
"""
if type(index) is not int:
raise TypeError('list indices must be integers')
if index < 0 or index >= self.nelems:
raise IndexError('list index out of range') | python | def _assertIndex(self, index):
"""Raise TypeError or IndexError if index is not an integer or out of
range for the number of elements in this array, respectively.
"""
if type(index) is not int:
raise TypeError('list indices must be integers')
if index < 0 or index >= self.nelems:
raise IndexError('list index out of range') | ['def', '_assertIndex', '(', 'self', ',', 'index', ')', ':', 'if', 'type', '(', 'index', ')', 'is', 'not', 'int', ':', 'raise', 'TypeError', '(', "'list indices must be integers'", ')', 'if', 'index', '<', '0', 'or', 'index', '>=', 'self', '.', 'nelems', ':', 'raise', 'IndexError', '(', "'list index out of range'", ')'] | Raise TypeError or IndexError if index is not an integer or out of
range for the number of elements in this array, respectively. | ['Raise', 'TypeError', 'or', 'IndexError', 'if', 'index', 'is', 'not', 'an', 'integer', 'or', 'out', 'of', 'range', 'for', 'the', 'number', 'of', 'elements', 'in', 'this', 'array', 'respectively', '.'] | train | https://github.com/NASA-AMMOS/AIT-Core/blob/9d85bd9c738e7a6a6fbdff672bea708238b02a3a/ait/core/dtype.py#L326-L333 |
6,259 | OpenHydrology/floodestimation | floodestimation/entities.py | Catchment.distance_to | def distance_to(self, other_catchment):
"""
Returns the distance between the centroids of two catchments in kilometers.
:param other_catchment: Catchment to calculate distance to
:type other_catchment: :class:`.Catchment`
:return: Distance between the catchments in km.
:rtype: float
"""
try:
if self.country == other_catchment.country:
try:
return 0.001 * hypot(self.descriptors.centroid_ngr.x - other_catchment.descriptors.centroid_ngr.x,
self.descriptors.centroid_ngr.y - other_catchment.descriptors.centroid_ngr.y)
except TypeError:
# In case no centroid available, just return infinity which is helpful in most cases
return float('+inf')
else:
# If the catchments are in a different country (e.g. `ni` versus `gb`) then set distance to infinity.
return float('+inf')
except (TypeError, KeyError):
raise InsufficientDataError("Catchment `descriptors` attribute must be set first.") | python | def distance_to(self, other_catchment):
"""
Returns the distance between the centroids of two catchments in kilometers.
:param other_catchment: Catchment to calculate distance to
:type other_catchment: :class:`.Catchment`
:return: Distance between the catchments in km.
:rtype: float
"""
try:
if self.country == other_catchment.country:
try:
return 0.001 * hypot(self.descriptors.centroid_ngr.x - other_catchment.descriptors.centroid_ngr.x,
self.descriptors.centroid_ngr.y - other_catchment.descriptors.centroid_ngr.y)
except TypeError:
# In case no centroid available, just return infinity which is helpful in most cases
return float('+inf')
else:
# If the catchments are in a different country (e.g. `ni` versus `gb`) then set distance to infinity.
return float('+inf')
except (TypeError, KeyError):
raise InsufficientDataError("Catchment `descriptors` attribute must be set first.") | ['def', 'distance_to', '(', 'self', ',', 'other_catchment', ')', ':', 'try', ':', 'if', 'self', '.', 'country', '==', 'other_catchment', '.', 'country', ':', 'try', ':', 'return', '0.001', '*', 'hypot', '(', 'self', '.', 'descriptors', '.', 'centroid_ngr', '.', 'x', '-', 'other_catchment', '.', 'descriptors', '.', 'centroid_ngr', '.', 'x', ',', 'self', '.', 'descriptors', '.', 'centroid_ngr', '.', 'y', '-', 'other_catchment', '.', 'descriptors', '.', 'centroid_ngr', '.', 'y', ')', 'except', 'TypeError', ':', '# In case no centroid available, just return infinity which is helpful in most cases', 'return', 'float', '(', "'+inf'", ')', 'else', ':', '# If the catchments are in a different country (e.g. `ni` versus `gb`) then set distance to infinity.', 'return', 'float', '(', "'+inf'", ')', 'except', '(', 'TypeError', ',', 'KeyError', ')', ':', 'raise', 'InsufficientDataError', '(', '"Catchment `descriptors` attribute must be set first."', ')'] | Returns the distance between the centroids of two catchments in kilometers.
:param other_catchment: Catchment to calculate distance to
:type other_catchment: :class:`.Catchment`
:return: Distance between the catchments in km.
:rtype: float | ['Returns', 'the', 'distance', 'between', 'the', 'centroids', 'of', 'two', 'catchments', 'in', 'kilometers', '.'] | train | https://github.com/OpenHydrology/floodestimation/blob/782da7c5abd1348923129efe89fb70003ebb088c/floodestimation/entities.py#L137-L158 |
6,260 | astraw/stdeb | stdeb/util.py | expand_tarball | def expand_tarball(tarball_fname,cwd=None):
"expand a tarball"
if tarball_fname.endswith('.gz'): opts = 'xzf'
elif tarball_fname.endswith('.bz2'): opts = 'xjf'
else: opts = 'xf'
args = ['/bin/tar',opts,tarball_fname]
process_command(args, cwd=cwd) | python | def expand_tarball(tarball_fname,cwd=None):
"expand a tarball"
if tarball_fname.endswith('.gz'): opts = 'xzf'
elif tarball_fname.endswith('.bz2'): opts = 'xjf'
else: opts = 'xf'
args = ['/bin/tar',opts,tarball_fname]
process_command(args, cwd=cwd) | ['def', 'expand_tarball', '(', 'tarball_fname', ',', 'cwd', '=', 'None', ')', ':', 'if', 'tarball_fname', '.', 'endswith', '(', "'.gz'", ')', ':', 'opts', '=', "'xzf'", 'elif', 'tarball_fname', '.', 'endswith', '(', "'.bz2'", ')', ':', 'opts', '=', "'xjf'", 'else', ':', 'opts', '=', "'xf'", 'args', '=', '[', "'/bin/tar'", ',', 'opts', ',', 'tarball_fname', ']', 'process_command', '(', 'args', ',', 'cwd', '=', 'cwd', ')'] | expand a tarball | ['expand', 'a', 'tarball'] | train | https://github.com/astraw/stdeb/blob/493ab88e8a60be053b1baef81fb39b45e17ceef5/stdeb/util.py#L466-L472 |
6,261 | gitpython-developers/GitPython | git/config.py | GitConfigParser.read | def read(self):
"""Reads the data stored in the files we have been initialized with. It will
ignore files that cannot be read, possibly leaving an empty configuration
:return: Nothing
:raise IOError: if a file cannot be handled"""
if self._is_initialized:
return
self._is_initialized = True
if not isinstance(self._file_or_files, (tuple, list)):
files_to_read = [self._file_or_files]
else:
files_to_read = list(self._file_or_files)
# end assure we have a copy of the paths to handle
seen = set(files_to_read)
num_read_include_files = 0
while files_to_read:
file_path = files_to_read.pop(0)
fp = file_path
file_ok = False
if hasattr(fp, "seek"):
self._read(fp, fp.name)
else:
# assume a path if it is not a file-object
try:
with open(file_path, 'rb') as fp:
file_ok = True
self._read(fp, fp.name)
except IOError:
continue
# Read includes and append those that we didn't handle yet
# We expect all paths to be normalized and absolute (and will assure that is the case)
if self._has_includes():
for _, include_path in self.items('include'):
if include_path.startswith('~'):
include_path = osp.expanduser(include_path)
if not osp.isabs(include_path):
if not file_ok:
continue
# end ignore relative paths if we don't know the configuration file path
assert osp.isabs(file_path), "Need absolute paths to be sure our cycle checks will work"
include_path = osp.join(osp.dirname(file_path), include_path)
# end make include path absolute
include_path = osp.normpath(include_path)
if include_path in seen or not os.access(include_path, os.R_OK):
continue
seen.add(include_path)
# insert included file to the top to be considered first
files_to_read.insert(0, include_path)
num_read_include_files += 1
# each include path in configuration file
# end handle includes
# END for each file object to read
# If there was no file included, we can safely write back (potentially) the configuration file
# without altering it's meaning
if num_read_include_files == 0:
self._merge_includes = False | python | def read(self):
"""Reads the data stored in the files we have been initialized with. It will
ignore files that cannot be read, possibly leaving an empty configuration
:return: Nothing
:raise IOError: if a file cannot be handled"""
if self._is_initialized:
return
self._is_initialized = True
if not isinstance(self._file_or_files, (tuple, list)):
files_to_read = [self._file_or_files]
else:
files_to_read = list(self._file_or_files)
# end assure we have a copy of the paths to handle
seen = set(files_to_read)
num_read_include_files = 0
while files_to_read:
file_path = files_to_read.pop(0)
fp = file_path
file_ok = False
if hasattr(fp, "seek"):
self._read(fp, fp.name)
else:
# assume a path if it is not a file-object
try:
with open(file_path, 'rb') as fp:
file_ok = True
self._read(fp, fp.name)
except IOError:
continue
# Read includes and append those that we didn't handle yet
# We expect all paths to be normalized and absolute (and will assure that is the case)
if self._has_includes():
for _, include_path in self.items('include'):
if include_path.startswith('~'):
include_path = osp.expanduser(include_path)
if not osp.isabs(include_path):
if not file_ok:
continue
# end ignore relative paths if we don't know the configuration file path
assert osp.isabs(file_path), "Need absolute paths to be sure our cycle checks will work"
include_path = osp.join(osp.dirname(file_path), include_path)
# end make include path absolute
include_path = osp.normpath(include_path)
if include_path in seen or not os.access(include_path, os.R_OK):
continue
seen.add(include_path)
# insert included file to the top to be considered first
files_to_read.insert(0, include_path)
num_read_include_files += 1
# each include path in configuration file
# end handle includes
# END for each file object to read
# If there was no file included, we can safely write back (potentially) the configuration file
# without altering it's meaning
if num_read_include_files == 0:
self._merge_includes = False | ['def', 'read', '(', 'self', ')', ':', 'if', 'self', '.', '_is_initialized', ':', 'return', 'self', '.', '_is_initialized', '=', 'True', 'if', 'not', 'isinstance', '(', 'self', '.', '_file_or_files', ',', '(', 'tuple', ',', 'list', ')', ')', ':', 'files_to_read', '=', '[', 'self', '.', '_file_or_files', ']', 'else', ':', 'files_to_read', '=', 'list', '(', 'self', '.', '_file_or_files', ')', '# end assure we have a copy of the paths to handle', 'seen', '=', 'set', '(', 'files_to_read', ')', 'num_read_include_files', '=', '0', 'while', 'files_to_read', ':', 'file_path', '=', 'files_to_read', '.', 'pop', '(', '0', ')', 'fp', '=', 'file_path', 'file_ok', '=', 'False', 'if', 'hasattr', '(', 'fp', ',', '"seek"', ')', ':', 'self', '.', '_read', '(', 'fp', ',', 'fp', '.', 'name', ')', 'else', ':', '# assume a path if it is not a file-object', 'try', ':', 'with', 'open', '(', 'file_path', ',', "'rb'", ')', 'as', 'fp', ':', 'file_ok', '=', 'True', 'self', '.', '_read', '(', 'fp', ',', 'fp', '.', 'name', ')', 'except', 'IOError', ':', 'continue', "# Read includes and append those that we didn't handle yet", '# We expect all paths to be normalized and absolute (and will assure that is the case)', 'if', 'self', '.', '_has_includes', '(', ')', ':', 'for', '_', ',', 'include_path', 'in', 'self', '.', 'items', '(', "'include'", ')', ':', 'if', 'include_path', '.', 'startswith', '(', "'~'", ')', ':', 'include_path', '=', 'osp', '.', 'expanduser', '(', 'include_path', ')', 'if', 'not', 'osp', '.', 'isabs', '(', 'include_path', ')', ':', 'if', 'not', 'file_ok', ':', 'continue', "# end ignore relative paths if we don't know the configuration file path", 'assert', 'osp', '.', 'isabs', '(', 'file_path', ')', ',', '"Need absolute paths to be sure our cycle checks will work"', 'include_path', '=', 'osp', '.', 'join', '(', 'osp', '.', 'dirname', '(', 'file_path', ')', ',', 'include_path', ')', '# end make include path absolute', 'include_path', '=', 'osp', '.', 'normpath', '(', 'include_path', ')', 'if', 'include_path', 'in', 'seen', 'or', 'not', 'os', '.', 'access', '(', 'include_path', ',', 'os', '.', 'R_OK', ')', ':', 'continue', 'seen', '.', 'add', '(', 'include_path', ')', '# insert included file to the top to be considered first', 'files_to_read', '.', 'insert', '(', '0', ',', 'include_path', ')', 'num_read_include_files', '+=', '1', '# each include path in configuration file', '# end handle includes', '# END for each file object to read', '# If there was no file included, we can safely write back (potentially) the configuration file', "# without altering it's meaning", 'if', 'num_read_include_files', '==', '0', ':', 'self', '.', '_merge_includes', '=', 'False'] | Reads the data stored in the files we have been initialized with. It will
ignore files that cannot be read, possibly leaving an empty configuration
:return: Nothing
:raise IOError: if a file cannot be handled | ['Reads', 'the', 'data', 'stored', 'in', 'the', 'files', 'we', 'have', 'been', 'initialized', 'with', '.', 'It', 'will', 'ignore', 'files', 'that', 'cannot', 'be', 'read', 'possibly', 'leaving', 'an', 'empty', 'configuration'] | train | https://github.com/gitpython-developers/GitPython/blob/1f66e25c25cde2423917ee18c4704fff83b837d1/git/config.py#L376-L437 |
6,262 | kislyuk/aegea | aegea/packages/github3/orgs.py | Organization.is_public_member | def is_public_member(self, login):
"""Check if the user with login ``login`` is a public member.
:returns: bool
"""
url = self._build_url('public_members', login, base_url=self._api)
return self._boolean(self._get(url), 204, 404) | python | def is_public_member(self, login):
"""Check if the user with login ``login`` is a public member.
:returns: bool
"""
url = self._build_url('public_members', login, base_url=self._api)
return self._boolean(self._get(url), 204, 404) | ['def', 'is_public_member', '(', 'self', ',', 'login', ')', ':', 'url', '=', 'self', '.', '_build_url', '(', "'public_members'", ',', 'login', ',', 'base_url', '=', 'self', '.', '_api', ')', 'return', 'self', '.', '_boolean', '(', 'self', '.', '_get', '(', 'url', ')', ',', '204', ',', '404', ')'] | Check if the user with login ``login`` is a public member.
:returns: bool | ['Check', 'if', 'the', 'user', 'with', 'login', 'login', 'is', 'a', 'public', 'member', '.'] | train | https://github.com/kislyuk/aegea/blob/94957e9dba036eae3052e2662c208b259c08399a/aegea/packages/github3/orgs.py#L424-L430 |
6,263 | danilobellini/dose | dose/watcher.py | to_unicode | def to_unicode(path, errors="replace"):
"""Given a bytestring/unicode path, return it as unicode."""
if isinstance(path, UNICODE):
return path
return path.decode(sys.getfilesystemencoding(), errors) | python | def to_unicode(path, errors="replace"):
"""Given a bytestring/unicode path, return it as unicode."""
if isinstance(path, UNICODE):
return path
return path.decode(sys.getfilesystemencoding(), errors) | ['def', 'to_unicode', '(', 'path', ',', 'errors', '=', '"replace"', ')', ':', 'if', 'isinstance', '(', 'path', ',', 'UNICODE', ')', ':', 'return', 'path', 'return', 'path', '.', 'decode', '(', 'sys', '.', 'getfilesystemencoding', '(', ')', ',', 'errors', ')'] | Given a bytestring/unicode path, return it as unicode. | ['Given', 'a', 'bytestring', '/', 'unicode', 'path', 'return', 'it', 'as', 'unicode', '.'] | train | https://github.com/danilobellini/dose/blob/141f48322f7812b7d32e3d5f065d4473a11102a4/dose/watcher.py#L8-L12 |
6,264 | openpaperwork/paperwork-backend | paperwork_backend/docsearch.py | DocIndexUpdater.commit | def commit(self, index_update=True, label_guesser_update=True):
"""
Apply the changes to the index
"""
logger.info("Index: Commiting changes")
self.docsearch.index.commit(index_update=index_update,
label_guesser_update=label_guesser_update) | python | def commit(self, index_update=True, label_guesser_update=True):
"""
Apply the changes to the index
"""
logger.info("Index: Commiting changes")
self.docsearch.index.commit(index_update=index_update,
label_guesser_update=label_guesser_update) | ['def', 'commit', '(', 'self', ',', 'index_update', '=', 'True', ',', 'label_guesser_update', '=', 'True', ')', ':', 'logger', '.', 'info', '(', '"Index: Commiting changes"', ')', 'self', '.', 'docsearch', '.', 'index', '.', 'commit', '(', 'index_update', '=', 'index_update', ',', 'label_guesser_update', '=', 'label_guesser_update', ')'] | Apply the changes to the index | ['Apply', 'the', 'changes', 'to', 'the', 'index'] | train | https://github.com/openpaperwork/paperwork-backend/blob/114b831e94e039e68b339751fd18250877abad76/paperwork_backend/docsearch.py#L224-L230 |
6,265 | noahbenson/neuropythy | neuropythy/geometry/mesh.py | path_trace | def path_trace(map_projection, pts, closed=False, meta_data=None):
'''
path_trace(proj, points) yields a path-trace object that represents the given path of points on
the given map projection proj.
The following options may be given:
* closed (default: False) specifies whether the points form a closed loop. If they do form
such a loop, the points should be given in the same ordering (counter-clockwise or
clockwise) that mesh vertices are given in; usually counter-clockwise.
* meta_data (default: None) specifies an optional additional meta-data map to append to the
object.
'''
return PathTrace(map_projection, pts, closed=closed, meta_data=meta_data) | python | def path_trace(map_projection, pts, closed=False, meta_data=None):
'''
path_trace(proj, points) yields a path-trace object that represents the given path of points on
the given map projection proj.
The following options may be given:
* closed (default: False) specifies whether the points form a closed loop. If they do form
such a loop, the points should be given in the same ordering (counter-clockwise or
clockwise) that mesh vertices are given in; usually counter-clockwise.
* meta_data (default: None) specifies an optional additional meta-data map to append to the
object.
'''
return PathTrace(map_projection, pts, closed=closed, meta_data=meta_data) | ['def', 'path_trace', '(', 'map_projection', ',', 'pts', ',', 'closed', '=', 'False', ',', 'meta_data', '=', 'None', ')', ':', 'return', 'PathTrace', '(', 'map_projection', ',', 'pts', ',', 'closed', '=', 'closed', ',', 'meta_data', '=', 'meta_data', ')'] | path_trace(proj, points) yields a path-trace object that represents the given path of points on
the given map projection proj.
The following options may be given:
* closed (default: False) specifies whether the points form a closed loop. If they do form
such a loop, the points should be given in the same ordering (counter-clockwise or
clockwise) that mesh vertices are given in; usually counter-clockwise.
* meta_data (default: None) specifies an optional additional meta-data map to append to the
object. | ['path_trace', '(', 'proj', 'points', ')', 'yields', 'a', 'path', '-', 'trace', 'object', 'that', 'represents', 'the', 'given', 'path', 'of', 'points', 'on', 'the', 'given', 'map', 'projection', 'proj', '.', 'The', 'following', 'options', 'may', 'be', 'given', ':', '*', 'closed', '(', 'default', ':', 'False', ')', 'specifies', 'whether', 'the', 'points', 'form', 'a', 'closed', 'loop', '.', 'If', 'they', 'do', 'form', 'such', 'a', 'loop', 'the', 'points', 'should', 'be', 'given', 'in', 'the', 'same', 'ordering', '(', 'counter', '-', 'clockwise', 'or', 'clockwise', ')', 'that', 'mesh', 'vertices', 'are', 'given', 'in', ';', 'usually', 'counter', '-', 'clockwise', '.', '*', 'meta_data', '(', 'default', ':', 'None', ')', 'specifies', 'an', 'optional', 'additional', 'meta', '-', 'data', 'map', 'to', 'append', 'to', 'the', 'object', '.'] | train | https://github.com/noahbenson/neuropythy/blob/b588889f6db36ddb9602ae4a72c1c0d3f41586b2/neuropythy/geometry/mesh.py#L3899-L3911 |
6,266 | kislyuk/aegea | aegea/packages/github3/repos/repo.py | Repository.hook | def hook(self, id_num):
"""Get a single hook.
:param int id_num: (required), id of the hook
:returns: :class:`Hook <github3.repos.hook.Hook>` if successful,
otherwise None
"""
json = None
if int(id_num) > 0:
url = self._build_url('hooks', str(id_num), base_url=self._api)
json = self._json(self._get(url), 200)
return Hook(json, self) if json else None | python | def hook(self, id_num):
"""Get a single hook.
:param int id_num: (required), id of the hook
:returns: :class:`Hook <github3.repos.hook.Hook>` if successful,
otherwise None
"""
json = None
if int(id_num) > 0:
url = self._build_url('hooks', str(id_num), base_url=self._api)
json = self._json(self._get(url), 200)
return Hook(json, self) if json else None | ['def', 'hook', '(', 'self', ',', 'id_num', ')', ':', 'json', '=', 'None', 'if', 'int', '(', 'id_num', ')', '>', '0', ':', 'url', '=', 'self', '.', '_build_url', '(', "'hooks'", ',', 'str', '(', 'id_num', ')', ',', 'base_url', '=', 'self', '.', '_api', ')', 'json', '=', 'self', '.', '_json', '(', 'self', '.', '_get', '(', 'url', ')', ',', '200', ')', 'return', 'Hook', '(', 'json', ',', 'self', ')', 'if', 'json', 'else', 'None'] | Get a single hook.
:param int id_num: (required), id of the hook
:returns: :class:`Hook <github3.repos.hook.Hook>` if successful,
otherwise None | ['Get', 'a', 'single', 'hook', '.'] | train | https://github.com/kislyuk/aegea/blob/94957e9dba036eae3052e2662c208b259c08399a/aegea/packages/github3/repos/repo.py#L996-L1007 |
6,267 | maxalbert/tohu | tohu/v2/custom_generator.py | add_new_next_method | def add_new_next_method(obj):
"""
TODO
"""
def new_next(self):
field_values = [next(g) for g in self.field_gens.values()]
return self.item_cls(*field_values)
obj.__next__ = new_next | python | def add_new_next_method(obj):
"""
TODO
"""
def new_next(self):
field_values = [next(g) for g in self.field_gens.values()]
return self.item_cls(*field_values)
obj.__next__ = new_next | ['def', 'add_new_next_method', '(', 'obj', ')', ':', 'def', 'new_next', '(', 'self', ')', ':', 'field_values', '=', '[', 'next', '(', 'g', ')', 'for', 'g', 'in', 'self', '.', 'field_gens', '.', 'values', '(', ')', ']', 'return', 'self', '.', 'item_cls', '(', '*', 'field_values', ')', 'obj', '.', '__next__', '=', 'new_next'] | TODO | ['TODO'] | train | https://github.com/maxalbert/tohu/blob/43380162fadec99cdd5c5c3152dd6b7d3a9d39a8/tohu/v2/custom_generator.py#L228-L237 |
6,268 | serkanyersen/underscore.py | src/underscore.py | underscore.functions | def functions(self):
""" Return a sorted list of the function names available on the object.
"""
names = []
for i, k in enumerate(self.obj):
if _(self.obj[k]).isCallable():
names.append(k)
return self._wrap(sorted(names)) | python | def functions(self):
""" Return a sorted list of the function names available on the object.
"""
names = []
for i, k in enumerate(self.obj):
if _(self.obj[k]).isCallable():
names.append(k)
return self._wrap(sorted(names)) | ['def', 'functions', '(', 'self', ')', ':', 'names', '=', '[', ']', 'for', 'i', ',', 'k', 'in', 'enumerate', '(', 'self', '.', 'obj', ')', ':', 'if', '_', '(', 'self', '.', 'obj', '[', 'k', ']', ')', '.', 'isCallable', '(', ')', ':', 'names', '.', 'append', '(', 'k', ')', 'return', 'self', '.', '_wrap', '(', 'sorted', '(', 'names', ')', ')'] | Return a sorted list of the function names available on the object. | ['Return', 'a', 'sorted', 'list', 'of', 'the', 'function', 'names', 'available', 'on', 'the', 'object', '.'] | train | https://github.com/serkanyersen/underscore.py/blob/07c25c3f0f789536e4ad47aa315faccc0da9602f/src/underscore.py#L973-L982 |
6,269 | sorgerlab/indra | indra/literature/elsevier_client.py | download_article | def download_article(id_val, id_type='doi', on_retry=False):
"""Low level function to get an XML article for a particular id.
Parameters
----------
id_val : str
The value of the id.
id_type : str
The type of id, such as pmid (a.k.a. pubmed_id), doi, or eid.
on_retry : bool
This function has a recursive retry feature, and this is the only time
this parameter should be used.
Returns
-------
content : str or None
If found, the content string is returned, otherwise, None is returned.
"""
if id_type == 'pmid':
id_type = 'pubmed_id'
url = '%s/%s' % (elsevier_article_url_fmt % id_type, id_val)
params = {'httpAccept': 'text/xml'}
res = requests.get(url, params, headers=ELSEVIER_KEYS)
if res.status_code == 404:
logger.info("Resource for %s not available on elsevier." % url)
return None
elif res.status_code == 429:
if not on_retry:
logger.warning("Broke the speed limit. Waiting half a second then "
"trying again...")
sleep(0.5)
return download_article(id_val, id_type, True)
else:
logger.error("Still breaking speed limit after waiting.")
logger.error("Elsevier response: %s" % res.text)
return None
elif res.status_code != 200:
logger.error('Could not download article %s: status code %d' %
(url, res.status_code))
logger.error('Elsevier response: %s' % res.text)
return None
else:
content_str = res.content.decode('utf-8')
if content_str.startswith('<service-error>'):
logger.error('Got a service error with 200 status: %s'
% content_str)
return None
# Return the XML content as a unicode string, assuming UTF-8 encoding
return content_str | python | def download_article(id_val, id_type='doi', on_retry=False):
"""Low level function to get an XML article for a particular id.
Parameters
----------
id_val : str
The value of the id.
id_type : str
The type of id, such as pmid (a.k.a. pubmed_id), doi, or eid.
on_retry : bool
This function has a recursive retry feature, and this is the only time
this parameter should be used.
Returns
-------
content : str or None
If found, the content string is returned, otherwise, None is returned.
"""
if id_type == 'pmid':
id_type = 'pubmed_id'
url = '%s/%s' % (elsevier_article_url_fmt % id_type, id_val)
params = {'httpAccept': 'text/xml'}
res = requests.get(url, params, headers=ELSEVIER_KEYS)
if res.status_code == 404:
logger.info("Resource for %s not available on elsevier." % url)
return None
elif res.status_code == 429:
if not on_retry:
logger.warning("Broke the speed limit. Waiting half a second then "
"trying again...")
sleep(0.5)
return download_article(id_val, id_type, True)
else:
logger.error("Still breaking speed limit after waiting.")
logger.error("Elsevier response: %s" % res.text)
return None
elif res.status_code != 200:
logger.error('Could not download article %s: status code %d' %
(url, res.status_code))
logger.error('Elsevier response: %s' % res.text)
return None
else:
content_str = res.content.decode('utf-8')
if content_str.startswith('<service-error>'):
logger.error('Got a service error with 200 status: %s'
% content_str)
return None
# Return the XML content as a unicode string, assuming UTF-8 encoding
return content_str | ['def', 'download_article', '(', 'id_val', ',', 'id_type', '=', "'doi'", ',', 'on_retry', '=', 'False', ')', ':', 'if', 'id_type', '==', "'pmid'", ':', 'id_type', '=', "'pubmed_id'", 'url', '=', "'%s/%s'", '%', '(', 'elsevier_article_url_fmt', '%', 'id_type', ',', 'id_val', ')', 'params', '=', '{', "'httpAccept'", ':', "'text/xml'", '}', 'res', '=', 'requests', '.', 'get', '(', 'url', ',', 'params', ',', 'headers', '=', 'ELSEVIER_KEYS', ')', 'if', 'res', '.', 'status_code', '==', '404', ':', 'logger', '.', 'info', '(', '"Resource for %s not available on elsevier."', '%', 'url', ')', 'return', 'None', 'elif', 'res', '.', 'status_code', '==', '429', ':', 'if', 'not', 'on_retry', ':', 'logger', '.', 'warning', '(', '"Broke the speed limit. Waiting half a second then "', '"trying again..."', ')', 'sleep', '(', '0.5', ')', 'return', 'download_article', '(', 'id_val', ',', 'id_type', ',', 'True', ')', 'else', ':', 'logger', '.', 'error', '(', '"Still breaking speed limit after waiting."', ')', 'logger', '.', 'error', '(', '"Elsevier response: %s"', '%', 'res', '.', 'text', ')', 'return', 'None', 'elif', 'res', '.', 'status_code', '!=', '200', ':', 'logger', '.', 'error', '(', "'Could not download article %s: status code %d'", '%', '(', 'url', ',', 'res', '.', 'status_code', ')', ')', 'logger', '.', 'error', '(', "'Elsevier response: %s'", '%', 'res', '.', 'text', ')', 'return', 'None', 'else', ':', 'content_str', '=', 'res', '.', 'content', '.', 'decode', '(', "'utf-8'", ')', 'if', 'content_str', '.', 'startswith', '(', "'<service-error>'", ')', ':', 'logger', '.', 'error', '(', "'Got a service error with 200 status: %s'", '%', 'content_str', ')', 'return', 'None', '# Return the XML content as a unicode string, assuming UTF-8 encoding', 'return', 'content_str'] | Low level function to get an XML article for a particular id.
Parameters
----------
id_val : str
The value of the id.
id_type : str
The type of id, such as pmid (a.k.a. pubmed_id), doi, or eid.
on_retry : bool
This function has a recursive retry feature, and this is the only time
this parameter should be used.
Returns
-------
content : str or None
If found, the content string is returned, otherwise, None is returned. | ['Low', 'level', 'function', 'to', 'get', 'an', 'XML', 'article', 'for', 'a', 'particular', 'id', '.'] | train | https://github.com/sorgerlab/indra/blob/79a70415832c5702d7a820c7c9ccc8e25010124b/indra/literature/elsevier_client.py#L110-L158 |
6,270 | GNS3/gns3-server | gns3server/compute/vmware/__init__.py | VMware.find_vmrun | def find_vmrun(self):
"""
Searches for vmrun.
:returns: path to vmrun
"""
# look for vmrun
vmrun_path = self.config.get_section_config("VMware").get("vmrun_path")
if not vmrun_path:
if sys.platform.startswith("win"):
vmrun_path = shutil.which("vmrun")
if vmrun_path is None:
# look for vmrun.exe using the VMware Workstation directory listed in the registry
vmrun_path = self._find_vmrun_registry(r"SOFTWARE\Wow6432Node\VMware, Inc.\VMware Workstation")
if vmrun_path is None:
# look for vmrun.exe using the VIX directory listed in the registry
vmrun_path = self._find_vmrun_registry(r"SOFTWARE\Wow6432Node\VMware, Inc.\VMware VIX")
elif sys.platform.startswith("darwin"):
vmrun_path = "/Applications/VMware Fusion.app/Contents/Library/vmrun"
else:
vmrun_path = "vmrun"
if vmrun_path and not os.path.isabs(vmrun_path):
vmrun_path = shutil.which(vmrun_path)
if not vmrun_path:
raise VMwareError("Could not find VMware vmrun, please make sure it is installed")
if not os.path.isfile(vmrun_path):
raise VMwareError("vmrun {} is not accessible".format(vmrun_path))
if not os.access(vmrun_path, os.X_OK):
raise VMwareError("vmrun is not executable")
if os.path.basename(vmrun_path).lower() not in ["vmrun", "vmrun.exe"]:
raise VMwareError("Invalid vmrun executable name {}".format(os.path.basename(vmrun_path)))
self._vmrun_path = vmrun_path
return vmrun_path | python | def find_vmrun(self):
"""
Searches for vmrun.
:returns: path to vmrun
"""
# look for vmrun
vmrun_path = self.config.get_section_config("VMware").get("vmrun_path")
if not vmrun_path:
if sys.platform.startswith("win"):
vmrun_path = shutil.which("vmrun")
if vmrun_path is None:
# look for vmrun.exe using the VMware Workstation directory listed in the registry
vmrun_path = self._find_vmrun_registry(r"SOFTWARE\Wow6432Node\VMware, Inc.\VMware Workstation")
if vmrun_path is None:
# look for vmrun.exe using the VIX directory listed in the registry
vmrun_path = self._find_vmrun_registry(r"SOFTWARE\Wow6432Node\VMware, Inc.\VMware VIX")
elif sys.platform.startswith("darwin"):
vmrun_path = "/Applications/VMware Fusion.app/Contents/Library/vmrun"
else:
vmrun_path = "vmrun"
if vmrun_path and not os.path.isabs(vmrun_path):
vmrun_path = shutil.which(vmrun_path)
if not vmrun_path:
raise VMwareError("Could not find VMware vmrun, please make sure it is installed")
if not os.path.isfile(vmrun_path):
raise VMwareError("vmrun {} is not accessible".format(vmrun_path))
if not os.access(vmrun_path, os.X_OK):
raise VMwareError("vmrun is not executable")
if os.path.basename(vmrun_path).lower() not in ["vmrun", "vmrun.exe"]:
raise VMwareError("Invalid vmrun executable name {}".format(os.path.basename(vmrun_path)))
self._vmrun_path = vmrun_path
return vmrun_path | ['def', 'find_vmrun', '(', 'self', ')', ':', '# look for vmrun', 'vmrun_path', '=', 'self', '.', 'config', '.', 'get_section_config', '(', '"VMware"', ')', '.', 'get', '(', '"vmrun_path"', ')', 'if', 'not', 'vmrun_path', ':', 'if', 'sys', '.', 'platform', '.', 'startswith', '(', '"win"', ')', ':', 'vmrun_path', '=', 'shutil', '.', 'which', '(', '"vmrun"', ')', 'if', 'vmrun_path', 'is', 'None', ':', '# look for vmrun.exe using the VMware Workstation directory listed in the registry', 'vmrun_path', '=', 'self', '.', '_find_vmrun_registry', '(', 'r"SOFTWARE\\Wow6432Node\\VMware, Inc.\\VMware Workstation"', ')', 'if', 'vmrun_path', 'is', 'None', ':', '# look for vmrun.exe using the VIX directory listed in the registry', 'vmrun_path', '=', 'self', '.', '_find_vmrun_registry', '(', 'r"SOFTWARE\\Wow6432Node\\VMware, Inc.\\VMware VIX"', ')', 'elif', 'sys', '.', 'platform', '.', 'startswith', '(', '"darwin"', ')', ':', 'vmrun_path', '=', '"/Applications/VMware Fusion.app/Contents/Library/vmrun"', 'else', ':', 'vmrun_path', '=', '"vmrun"', 'if', 'vmrun_path', 'and', 'not', 'os', '.', 'path', '.', 'isabs', '(', 'vmrun_path', ')', ':', 'vmrun_path', '=', 'shutil', '.', 'which', '(', 'vmrun_path', ')', 'if', 'not', 'vmrun_path', ':', 'raise', 'VMwareError', '(', '"Could not find VMware vmrun, please make sure it is installed"', ')', 'if', 'not', 'os', '.', 'path', '.', 'isfile', '(', 'vmrun_path', ')', ':', 'raise', 'VMwareError', '(', '"vmrun {} is not accessible"', '.', 'format', '(', 'vmrun_path', ')', ')', 'if', 'not', 'os', '.', 'access', '(', 'vmrun_path', ',', 'os', '.', 'X_OK', ')', ':', 'raise', 'VMwareError', '(', '"vmrun is not executable"', ')', 'if', 'os', '.', 'path', '.', 'basename', '(', 'vmrun_path', ')', '.', 'lower', '(', ')', 'not', 'in', '[', '"vmrun"', ',', '"vmrun.exe"', ']', ':', 'raise', 'VMwareError', '(', '"Invalid vmrun executable name {}"', '.', 'format', '(', 'os', '.', 'path', '.', 'basename', '(', 'vmrun_path', ')', ')', ')', 'self', '.', '_vmrun_path', '=', 'vmrun_path', 'return', 'vmrun_path'] | Searches for vmrun.
:returns: path to vmrun | ['Searches', 'for', 'vmrun', '.'] | train | https://github.com/GNS3/gns3-server/blob/a221678448fb5d24e977ef562f81d56aacc89ab1/gns3server/compute/vmware/__init__.py#L87-L123 |
6,271 | Kozea/pygal | pygal/colors.py | unparse_color | def unparse_color(r, g, b, a, type):
"""
Take the r, g, b, a color values and give back
a type css color string. This is the inverse function of parse_color
"""
if type == '#rgb':
# Don't lose precision on rgb shortcut
if r % 17 == 0 and g % 17 == 0 and b % 17 == 0:
return '#%x%x%x' % (int(r / 17), int(g / 17), int(b / 17))
type = '#rrggbb'
if type == '#rgba':
if r % 17 == 0 and g % 17 == 0 and b % 17 == 0:
return '#%x%x%x%x' % (
int(r / 17), int(g / 17), int(b / 17), int(a * 15)
)
type = '#rrggbbaa'
if type == '#rrggbb':
return '#%02x%02x%02x' % (r, g, b)
if type == '#rrggbbaa':
return '#%02x%02x%02x%02x' % (r, g, b, int(a * 255))
if type == 'rgb':
return 'rgb(%d, %d, %d)' % (r, g, b)
if type == 'rgba':
return 'rgba(%d, %d, %d, %g)' % (r, g, b, a) | python | def unparse_color(r, g, b, a, type):
"""
Take the r, g, b, a color values and give back
a type css color string. This is the inverse function of parse_color
"""
if type == '#rgb':
# Don't lose precision on rgb shortcut
if r % 17 == 0 and g % 17 == 0 and b % 17 == 0:
return '#%x%x%x' % (int(r / 17), int(g / 17), int(b / 17))
type = '#rrggbb'
if type == '#rgba':
if r % 17 == 0 and g % 17 == 0 and b % 17 == 0:
return '#%x%x%x%x' % (
int(r / 17), int(g / 17), int(b / 17), int(a * 15)
)
type = '#rrggbbaa'
if type == '#rrggbb':
return '#%02x%02x%02x' % (r, g, b)
if type == '#rrggbbaa':
return '#%02x%02x%02x%02x' % (r, g, b, int(a * 255))
if type == 'rgb':
return 'rgb(%d, %d, %d)' % (r, g, b)
if type == 'rgba':
return 'rgba(%d, %d, %d, %g)' % (r, g, b, a) | ['def', 'unparse_color', '(', 'r', ',', 'g', ',', 'b', ',', 'a', ',', 'type', ')', ':', 'if', 'type', '==', "'#rgb'", ':', "# Don't lose precision on rgb shortcut", 'if', 'r', '%', '17', '==', '0', 'and', 'g', '%', '17', '==', '0', 'and', 'b', '%', '17', '==', '0', ':', 'return', "'#%x%x%x'", '%', '(', 'int', '(', 'r', '/', '17', ')', ',', 'int', '(', 'g', '/', '17', ')', ',', 'int', '(', 'b', '/', '17', ')', ')', 'type', '=', "'#rrggbb'", 'if', 'type', '==', "'#rgba'", ':', 'if', 'r', '%', '17', '==', '0', 'and', 'g', '%', '17', '==', '0', 'and', 'b', '%', '17', '==', '0', ':', 'return', "'#%x%x%x%x'", '%', '(', 'int', '(', 'r', '/', '17', ')', ',', 'int', '(', 'g', '/', '17', ')', ',', 'int', '(', 'b', '/', '17', ')', ',', 'int', '(', 'a', '*', '15', ')', ')', 'type', '=', "'#rrggbbaa'", 'if', 'type', '==', "'#rrggbb'", ':', 'return', "'#%02x%02x%02x'", '%', '(', 'r', ',', 'g', ',', 'b', ')', 'if', 'type', '==', "'#rrggbbaa'", ':', 'return', "'#%02x%02x%02x%02x'", '%', '(', 'r', ',', 'g', ',', 'b', ',', 'int', '(', 'a', '*', '255', ')', ')', 'if', 'type', '==', "'rgb'", ':', 'return', "'rgb(%d, %d, %d)'", '%', '(', 'r', ',', 'g', ',', 'b', ')', 'if', 'type', '==', "'rgba'", ':', 'return', "'rgba(%d, %d, %d, %g)'", '%', '(', 'r', ',', 'g', ',', 'b', ',', 'a', ')'] | Take the r, g, b, a color values and give back
a type css color string. This is the inverse function of parse_color | ['Take', 'the', 'r', 'g', 'b', 'a', 'color', 'values', 'and', 'give', 'back', 'a', 'type', 'css', 'color', 'string', '.', 'This', 'is', 'the', 'inverse', 'function', 'of', 'parse_color'] | train | https://github.com/Kozea/pygal/blob/5e25c98a59a0642eecd9fcc5dbfeeb2190fbb5e7/pygal/colors.py#L127-L155 |
6,272 | Anaconda-Platform/anaconda-client | binstar_client/inspect_package/pypi.py | parse_specification | def parse_specification(spec):
"""
Parse a requirement from a python distribution metadata and return a
tuple with name, extras, constraints, marker and url components.
This method does not enforce strict specifications but extracts the
information which is assumed to be *correct*. As such no errors are raised.
Example
-------
spec = 'requests[security, tests] >=3.3.0 ; foo >= 2.7 or bar == 1'
('requests', ['security', 'pyfoo'], '>=3.3.0', 'foo >= 2.7 or bar == 1', '')
"""
name, extras, const = spec, [], ''
# Remove excess whitespace
spec = ' '.join(p for p in spec.split(' ') if p).strip()
# Extract marker (Assumes that there can only be one ';' inside the spec)
spec, marker = split_spec(spec, ';')
# Extract url (Assumes that there can only be one '@' inside the spec)
spec, url = split_spec(spec, '@')
# Find name, extras and constraints
r = PARTIAL_PYPI_SPEC_PATTERN.match(spec)
if r:
# Normalize name
name = r.group('name')
# Clean extras
extras = r.group('extras')
extras = [e.strip() for e in extras.split(',') if e] if extras else []
# Clean constraints
const = r.group('constraints')
const = ''.join(c for c in const.split(' ') if c).strip()
if const.startswith('(') and const.endswith(')'):
# Remove parens
const = const[1:-1]
return name, extras, const, marker, url | python | def parse_specification(spec):
"""
Parse a requirement from a python distribution metadata and return a
tuple with name, extras, constraints, marker and url components.
This method does not enforce strict specifications but extracts the
information which is assumed to be *correct*. As such no errors are raised.
Example
-------
spec = 'requests[security, tests] >=3.3.0 ; foo >= 2.7 or bar == 1'
('requests', ['security', 'pyfoo'], '>=3.3.0', 'foo >= 2.7 or bar == 1', '')
"""
name, extras, const = spec, [], ''
# Remove excess whitespace
spec = ' '.join(p for p in spec.split(' ') if p).strip()
# Extract marker (Assumes that there can only be one ';' inside the spec)
spec, marker = split_spec(spec, ';')
# Extract url (Assumes that there can only be one '@' inside the spec)
spec, url = split_spec(spec, '@')
# Find name, extras and constraints
r = PARTIAL_PYPI_SPEC_PATTERN.match(spec)
if r:
# Normalize name
name = r.group('name')
# Clean extras
extras = r.group('extras')
extras = [e.strip() for e in extras.split(',') if e] if extras else []
# Clean constraints
const = r.group('constraints')
const = ''.join(c for c in const.split(' ') if c).strip()
if const.startswith('(') and const.endswith(')'):
# Remove parens
const = const[1:-1]
return name, extras, const, marker, url | ['def', 'parse_specification', '(', 'spec', ')', ':', 'name', ',', 'extras', ',', 'const', '=', 'spec', ',', '[', ']', ',', "''", '# Remove excess whitespace', 'spec', '=', "' '", '.', 'join', '(', 'p', 'for', 'p', 'in', 'spec', '.', 'split', '(', "' '", ')', 'if', 'p', ')', '.', 'strip', '(', ')', "# Extract marker (Assumes that there can only be one ';' inside the spec)", 'spec', ',', 'marker', '=', 'split_spec', '(', 'spec', ',', "';'", ')', "# Extract url (Assumes that there can only be one '@' inside the spec)", 'spec', ',', 'url', '=', 'split_spec', '(', 'spec', ',', "'@'", ')', '# Find name, extras and constraints', 'r', '=', 'PARTIAL_PYPI_SPEC_PATTERN', '.', 'match', '(', 'spec', ')', 'if', 'r', ':', '# Normalize name', 'name', '=', 'r', '.', 'group', '(', "'name'", ')', '# Clean extras', 'extras', '=', 'r', '.', 'group', '(', "'extras'", ')', 'extras', '=', '[', 'e', '.', 'strip', '(', ')', 'for', 'e', 'in', 'extras', '.', 'split', '(', "','", ')', 'if', 'e', ']', 'if', 'extras', 'else', '[', ']', '# Clean constraints', 'const', '=', 'r', '.', 'group', '(', "'constraints'", ')', 'const', '=', "''", '.', 'join', '(', 'c', 'for', 'c', 'in', 'const', '.', 'split', '(', "' '", ')', 'if', 'c', ')', '.', 'strip', '(', ')', 'if', 'const', '.', 'startswith', '(', "'('", ')', 'and', 'const', '.', 'endswith', '(', "')'", ')', ':', '# Remove parens', 'const', '=', 'const', '[', '1', ':', '-', '1', ']', 'return', 'name', ',', 'extras', ',', 'const', ',', 'marker', ',', 'url'] | Parse a requirement from a python distribution metadata and return a
tuple with name, extras, constraints, marker and url components.
This method does not enforce strict specifications but extracts the
information which is assumed to be *correct*. As such no errors are raised.
Example
-------
spec = 'requests[security, tests] >=3.3.0 ; foo >= 2.7 or bar == 1'
('requests', ['security', 'pyfoo'], '>=3.3.0', 'foo >= 2.7 or bar == 1', '') | ['Parse', 'a', 'requirement', 'from', 'a', 'python', 'distribution', 'metadata', 'and', 'return', 'a', 'tuple', 'with', 'name', 'extras', 'constraints', 'marker', 'and', 'url', 'components', '.'] | train | https://github.com/Anaconda-Platform/anaconda-client/blob/b276f0572744c73c184a8b43a897cfa7fc1dc523/binstar_client/inspect_package/pypi.py#L66-L108 |
6,273 | HazyResearch/fonduer | src/fonduer/utils/data_model_utils/visual.py | same_page | def same_page(c):
"""Return true if all the components of c are on the same page of the document.
Page numbers are based on the PDF rendering of the document. If a PDF file is
provided, it is used. Otherwise, if only a HTML/XML document is provided, a
PDF is created and then used to determine the page number of a Mention.
:param c: The candidate to evaluate
:rtype: boolean
"""
return all(
[
_to_span(c[i]).sentence.is_visual()
and bbox_from_span(_to_span(c[i])).page
== bbox_from_span(_to_span(c[0])).page
for i in range(len(c))
]
) | python | def same_page(c):
"""Return true if all the components of c are on the same page of the document.
Page numbers are based on the PDF rendering of the document. If a PDF file is
provided, it is used. Otherwise, if only a HTML/XML document is provided, a
PDF is created and then used to determine the page number of a Mention.
:param c: The candidate to evaluate
:rtype: boolean
"""
return all(
[
_to_span(c[i]).sentence.is_visual()
and bbox_from_span(_to_span(c[i])).page
== bbox_from_span(_to_span(c[0])).page
for i in range(len(c))
]
) | ['def', 'same_page', '(', 'c', ')', ':', 'return', 'all', '(', '[', '_to_span', '(', 'c', '[', 'i', ']', ')', '.', 'sentence', '.', 'is_visual', '(', ')', 'and', 'bbox_from_span', '(', '_to_span', '(', 'c', '[', 'i', ']', ')', ')', '.', 'page', '==', 'bbox_from_span', '(', '_to_span', '(', 'c', '[', '0', ']', ')', ')', '.', 'page', 'for', 'i', 'in', 'range', '(', 'len', '(', 'c', ')', ')', ']', ')'] | Return true if all the components of c are on the same page of the document.
Page numbers are based on the PDF rendering of the document. If a PDF file is
provided, it is used. Otherwise, if only a HTML/XML document is provided, a
PDF is created and then used to determine the page number of a Mention.
:param c: The candidate to evaluate
:rtype: boolean | ['Return', 'true', 'if', 'all', 'the', 'components', 'of', 'c', 'are', 'on', 'the', 'same', 'page', 'of', 'the', 'document', '.'] | train | https://github.com/HazyResearch/fonduer/blob/4520f86a716f03dcca458a9f4bddac75b4e7068f/src/fonduer/utils/data_model_utils/visual.py#L148-L165 |
6,274 | KeplerGO/K2fov | K2fov/fov.py | KeplerFov.colRowIsOnSciencePixel | def colRowIsOnSciencePixel(self, col, row, padding=DEFAULT_PADDING):
"""Is col row on a science pixel?
Ranges taken from Fig 25 or Instrument Handbook (p50)
Padding allows for the fact that distortion means the
results from getColRowWithinChannel can be off by a bit.
Setting padding > 0 means that objects that are computed
to lie a small amount off silicon will return True.
To be conservative, set padding to negative
"""
if col < 12. - padding or col > 1111 + padding:
return False
if row < 20 - padding or row > 1043 + padding:
return False
return True | python | def colRowIsOnSciencePixel(self, col, row, padding=DEFAULT_PADDING):
"""Is col row on a science pixel?
Ranges taken from Fig 25 or Instrument Handbook (p50)
Padding allows for the fact that distortion means the
results from getColRowWithinChannel can be off by a bit.
Setting padding > 0 means that objects that are computed
to lie a small amount off silicon will return True.
To be conservative, set padding to negative
"""
if col < 12. - padding or col > 1111 + padding:
return False
if row < 20 - padding or row > 1043 + padding:
return False
return True | ['def', 'colRowIsOnSciencePixel', '(', 'self', ',', 'col', ',', 'row', ',', 'padding', '=', 'DEFAULT_PADDING', ')', ':', 'if', 'col', '<', '12.', '-', 'padding', 'or', 'col', '>', '1111', '+', 'padding', ':', 'return', 'False', 'if', 'row', '<', '20', '-', 'padding', 'or', 'row', '>', '1043', '+', 'padding', ':', 'return', 'False', 'return', 'True'] | Is col row on a science pixel?
Ranges taken from Fig 25 or Instrument Handbook (p50)
Padding allows for the fact that distortion means the
results from getColRowWithinChannel can be off by a bit.
Setting padding > 0 means that objects that are computed
to lie a small amount off silicon will return True.
To be conservative, set padding to negative | ['Is', 'col', 'row', 'on', 'a', 'science', 'pixel?'] | train | https://github.com/KeplerGO/K2fov/blob/fb122b35687340e0357cba9e0dd47b3be0760693/K2fov/fov.py#L399-L416 |
6,275 | limodou/uliweb | uliweb/contrib/generic/__init__.py | MultiView._query_view | def _query_view(self, model, **kwargs):
"""
:param model:
:return: (query, condition)
Default use QueryForm
"""
QueryForm = functions.get_form('QueryForm')
if 'form_cls' not in kwargs:
kwargs['form_cls'] = QueryForm
query = functions.QueryView(model, **kwargs)
return query | python | def _query_view(self, model, **kwargs):
"""
:param model:
:return: (query, condition)
Default use QueryForm
"""
QueryForm = functions.get_form('QueryForm')
if 'form_cls' not in kwargs:
kwargs['form_cls'] = QueryForm
query = functions.QueryView(model, **kwargs)
return query | ['def', '_query_view', '(', 'self', ',', 'model', ',', '*', '*', 'kwargs', ')', ':', 'QueryForm', '=', 'functions', '.', 'get_form', '(', "'QueryForm'", ')', 'if', "'form_cls'", 'not', 'in', 'kwargs', ':', 'kwargs', '[', "'form_cls'", ']', '=', 'QueryForm', 'query', '=', 'functions', '.', 'QueryView', '(', 'model', ',', '*', '*', 'kwargs', ')', 'return', 'query'] | :param model:
:return: (query, condition)
Default use QueryForm | [':', 'param', 'model', ':', ':', 'return', ':', '(', 'query', 'condition', ')'] | train | https://github.com/limodou/uliweb/blob/34472f25e4bc0b954a35346672f94e84ef18b076/uliweb/contrib/generic/__init__.py#L115-L127 |
6,276 | thautwarm/Redy | Redy/Magic/Classic.py | singleton_init_by | def singleton_init_by(init_fn=None):
"""
>>> from Redy.Magic.Classic import singleton
>>> @singleton
>>> class S:
>>> pass
>>> assert isinstance(S, S)
"""
if not init_fn:
def wrap_init(origin_init):
return origin_init
else:
def wrap_init(origin_init):
def __init__(self):
origin_init(self)
init_fn(self)
return __init__
def inner(cls_def: type):
if not hasattr(cls_def, '__instancecheck__') or isinstance(cls_def.__instancecheck__,
(types.BuiltinMethodType, _slot_wrapper)):
def __instancecheck__(self, instance):
return instance is self
cls_def.__instancecheck__ = __instancecheck__
_origin_init = cls_def.__init__
cls_def.__init__ = wrap_init(_origin_init)
return cls_def()
return inner | python | def singleton_init_by(init_fn=None):
"""
>>> from Redy.Magic.Classic import singleton
>>> @singleton
>>> class S:
>>> pass
>>> assert isinstance(S, S)
"""
if not init_fn:
def wrap_init(origin_init):
return origin_init
else:
def wrap_init(origin_init):
def __init__(self):
origin_init(self)
init_fn(self)
return __init__
def inner(cls_def: type):
if not hasattr(cls_def, '__instancecheck__') or isinstance(cls_def.__instancecheck__,
(types.BuiltinMethodType, _slot_wrapper)):
def __instancecheck__(self, instance):
return instance is self
cls_def.__instancecheck__ = __instancecheck__
_origin_init = cls_def.__init__
cls_def.__init__ = wrap_init(_origin_init)
return cls_def()
return inner | ['def', 'singleton_init_by', '(', 'init_fn', '=', 'None', ')', ':', 'if', 'not', 'init_fn', ':', 'def', 'wrap_init', '(', 'origin_init', ')', ':', 'return', 'origin_init', 'else', ':', 'def', 'wrap_init', '(', 'origin_init', ')', ':', 'def', '__init__', '(', 'self', ')', ':', 'origin_init', '(', 'self', ')', 'init_fn', '(', 'self', ')', 'return', '__init__', 'def', 'inner', '(', 'cls_def', ':', 'type', ')', ':', 'if', 'not', 'hasattr', '(', 'cls_def', ',', "'__instancecheck__'", ')', 'or', 'isinstance', '(', 'cls_def', '.', '__instancecheck__', ',', '(', 'types', '.', 'BuiltinMethodType', ',', '_slot_wrapper', ')', ')', ':', 'def', '__instancecheck__', '(', 'self', ',', 'instance', ')', ':', 'return', 'instance', 'is', 'self', 'cls_def', '.', '__instancecheck__', '=', '__instancecheck__', '_origin_init', '=', 'cls_def', '.', '__init__', 'cls_def', '.', '__init__', '=', 'wrap_init', '(', '_origin_init', ')', 'return', 'cls_def', '(', ')', 'return', 'inner'] | >>> from Redy.Magic.Classic import singleton
>>> @singleton
>>> class S:
>>> pass
>>> assert isinstance(S, S) | ['>>>', 'from', 'Redy', '.', 'Magic', '.', 'Classic', 'import', 'singleton', '>>>'] | train | https://github.com/thautwarm/Redy/blob/8beee5c5f752edfd2754bb1e6b5f4acb016a7770/Redy/Magic/Classic.py#L18-L51 |
6,277 | Feneric/doxypypy | doxypypy/doxypypy.py | AstWalker._checkIfCode | def _checkIfCode(self, inCodeBlockObj):
"""Checks whether or not a given line appears to be Python code."""
while True:
line, lines, lineNum = (yield)
testLineNum = 1
currentLineNum = 0
testLine = line.strip()
lineOfCode = None
while lineOfCode is None:
match = AstWalker.__errorLineRE.match(testLine)
if not testLine or testLine == '...' or match:
# These are ambiguous.
line, lines, lineNum = (yield)
testLine = line.strip()
#testLineNum = 1
elif testLine.startswith('>>>'):
# This is definitely code.
lineOfCode = True
else:
try:
compLine = compile_command(testLine)
if compLine and lines[currentLineNum].strip().startswith('#'):
lineOfCode = True
else:
line, lines, lineNum = (yield)
line = line.strip()
if line.startswith('>>>'):
# Definitely code, don't compile further.
lineOfCode = True
else:
testLine += linesep + line
testLine = testLine.strip()
testLineNum += 1
except (SyntaxError, RuntimeError):
# This is definitely not code.
lineOfCode = False
except Exception:
# Other errors are ambiguous.
line, lines, lineNum = (yield)
testLine = line.strip()
#testLineNum = 1
currentLineNum = lineNum - testLineNum
if not inCodeBlockObj[0] and lineOfCode:
inCodeBlockObj[0] = True
lines[currentLineNum] = '{0}{1}# @code{1}'.format(
lines[currentLineNum],
linesep
)
elif inCodeBlockObj[0] and lineOfCode is False:
# None is ambiguous, so strict checking
# against False is necessary.
inCodeBlockObj[0] = False
lines[currentLineNum] = '{0}{1}# @endcode{1}'.format(
lines[currentLineNum],
linesep
) | python | def _checkIfCode(self, inCodeBlockObj):
"""Checks whether or not a given line appears to be Python code."""
while True:
line, lines, lineNum = (yield)
testLineNum = 1
currentLineNum = 0
testLine = line.strip()
lineOfCode = None
while lineOfCode is None:
match = AstWalker.__errorLineRE.match(testLine)
if not testLine or testLine == '...' or match:
# These are ambiguous.
line, lines, lineNum = (yield)
testLine = line.strip()
#testLineNum = 1
elif testLine.startswith('>>>'):
# This is definitely code.
lineOfCode = True
else:
try:
compLine = compile_command(testLine)
if compLine and lines[currentLineNum].strip().startswith('#'):
lineOfCode = True
else:
line, lines, lineNum = (yield)
line = line.strip()
if line.startswith('>>>'):
# Definitely code, don't compile further.
lineOfCode = True
else:
testLine += linesep + line
testLine = testLine.strip()
testLineNum += 1
except (SyntaxError, RuntimeError):
# This is definitely not code.
lineOfCode = False
except Exception:
# Other errors are ambiguous.
line, lines, lineNum = (yield)
testLine = line.strip()
#testLineNum = 1
currentLineNum = lineNum - testLineNum
if not inCodeBlockObj[0] and lineOfCode:
inCodeBlockObj[0] = True
lines[currentLineNum] = '{0}{1}# @code{1}'.format(
lines[currentLineNum],
linesep
)
elif inCodeBlockObj[0] and lineOfCode is False:
# None is ambiguous, so strict checking
# against False is necessary.
inCodeBlockObj[0] = False
lines[currentLineNum] = '{0}{1}# @endcode{1}'.format(
lines[currentLineNum],
linesep
) | ['def', '_checkIfCode', '(', 'self', ',', 'inCodeBlockObj', ')', ':', 'while', 'True', ':', 'line', ',', 'lines', ',', 'lineNum', '=', '(', 'yield', ')', 'testLineNum', '=', '1', 'currentLineNum', '=', '0', 'testLine', '=', 'line', '.', 'strip', '(', ')', 'lineOfCode', '=', 'None', 'while', 'lineOfCode', 'is', 'None', ':', 'match', '=', 'AstWalker', '.', '__errorLineRE', '.', 'match', '(', 'testLine', ')', 'if', 'not', 'testLine', 'or', 'testLine', '==', "'...'", 'or', 'match', ':', '# These are ambiguous.', 'line', ',', 'lines', ',', 'lineNum', '=', '(', 'yield', ')', 'testLine', '=', 'line', '.', 'strip', '(', ')', '#testLineNum = 1', 'elif', 'testLine', '.', 'startswith', '(', "'>>>'", ')', ':', '# This is definitely code.', 'lineOfCode', '=', 'True', 'else', ':', 'try', ':', 'compLine', '=', 'compile_command', '(', 'testLine', ')', 'if', 'compLine', 'and', 'lines', '[', 'currentLineNum', ']', '.', 'strip', '(', ')', '.', 'startswith', '(', "'#'", ')', ':', 'lineOfCode', '=', 'True', 'else', ':', 'line', ',', 'lines', ',', 'lineNum', '=', '(', 'yield', ')', 'line', '=', 'line', '.', 'strip', '(', ')', 'if', 'line', '.', 'startswith', '(', "'>>>'", ')', ':', "# Definitely code, don't compile further.", 'lineOfCode', '=', 'True', 'else', ':', 'testLine', '+=', 'linesep', '+', 'line', 'testLine', '=', 'testLine', '.', 'strip', '(', ')', 'testLineNum', '+=', '1', 'except', '(', 'SyntaxError', ',', 'RuntimeError', ')', ':', '# This is definitely not code.', 'lineOfCode', '=', 'False', 'except', 'Exception', ':', '# Other errors are ambiguous.', 'line', ',', 'lines', ',', 'lineNum', '=', '(', 'yield', ')', 'testLine', '=', 'line', '.', 'strip', '(', ')', '#testLineNum = 1', 'currentLineNum', '=', 'lineNum', '-', 'testLineNum', 'if', 'not', 'inCodeBlockObj', '[', '0', ']', 'and', 'lineOfCode', ':', 'inCodeBlockObj', '[', '0', ']', '=', 'True', 'lines', '[', 'currentLineNum', ']', '=', "'{0}{1}# @code{1}'", '.', 'format', '(', 'lines', '[', 'currentLineNum', ']', ',', 'linesep', ')', 'elif', 'inCodeBlockObj', '[', '0', ']', 'and', 'lineOfCode', 'is', 'False', ':', '# None is ambiguous, so strict checking', '# against False is necessary.', 'inCodeBlockObj', '[', '0', ']', '=', 'False', 'lines', '[', 'currentLineNum', ']', '=', "'{0}{1}# @endcode{1}'", '.', 'format', '(', 'lines', '[', 'currentLineNum', ']', ',', 'linesep', ')'] | Checks whether or not a given line appears to be Python code. | ['Checks', 'whether', 'or', 'not', 'a', 'given', 'line', 'appears', 'to', 'be', 'Python', 'code', '.'] | train | https://github.com/Feneric/doxypypy/blob/a8555b15fa2a758ea8392372de31c0f635cc0d93/doxypypy/doxypypy.py#L121-L176 |
6,278 | openstack/networking-cisco | networking_cisco/plugins/cisco/db/l3/ha_db.py | HA_db_mixin._update_redundancy_routers | def _update_redundancy_routers(self, context, updated_router,
update_specification, requested_ha_settings,
updated_router_db, gateway_changed):
"""To be called in update_router() AFTER router has been
updated in DB.
"""
router_requested = update_specification['router']
ha_settings_db = updated_router_db.ha_settings
ha_enabled_requested = requested_ha_settings.get(ha.ENABLED, False)
if not (updated_router[ha.ENABLED] or ha_enabled_requested):
# No HA currently enabled and no HA requested so we're done
return
# The redundancy routers need interfaces on the same networks as the
# user visible router.
ports = self._get_router_interfaces(updated_router_db)
e_context = context.elevated()
if not updated_router[ha.ENABLED] and ha_enabled_requested:
# No HA currently enabled but HA requested
router_requested.update(requested_ha_settings)
router_requested[EXTERNAL_GW_INFO] = (
updated_router[EXTERNAL_GW_INFO])
requested_ha_settings = self._ensure_create_ha_compliant(
router_requested, updated_router_db.hosting_info.router_type)
self._create_redundancy_routers(
e_context, updated_router, requested_ha_settings,
updated_router_db, ports, expire_db=True)
return
rr_ids = self._get_redundancy_router_ids(context, updated_router['id'])
ha_details_update_spec = requested_ha_settings.get(ha.DETAILS)
if (updated_router[ha.ENABLED] and not requested_ha_settings.get(
ha.ENABLED, updated_router[ha.ENABLED])):
# HA currently enabled but HA disable requested
# delete ha settings and extra port for gateway (VIP) port
self._delete_ha_group(e_context, updated_router_db.gw_port_id)
self._remove_redundancy_routers(e_context, rr_ids, ports, True)
with context.session.begin(subtransactions=True):
context.session.delete(ha_settings_db)
elif ha_details_update_spec:
# HA currently enabled and HA setting update (other than
# disable HA) requested
old_redundancy_level = ha_settings_db.redundancy_level
ha_settings_db.update(ha_details_update_spec)
diff = (ha_details_update_spec.get(ha.REDUNDANCY_LEVEL,
old_redundancy_level) -
old_redundancy_level)
with context.session.begin(subtransactions=True):
context.session.add(ha_settings_db)
if diff < 0:
# Remove -diff redundancy routers
#TODO(bobmel): Ensure currently active router is excluded
to_remove = rr_ids[len(rr_ids) + diff:]
rr_ids = rr_ids[:len(rr_ids) + diff]
self._remove_redundancy_routers(e_context, to_remove, ports)
elif diff > 0:
# Add diff redundancy routers
start = old_redundancy_level + 1
stop = start + diff
self._add_redundancy_routers(e_context, start, stop,
updated_router, ports,
ha_settings_db, False)
if gateway_changed is True:
self._change_ha_for_gateway(e_context, updated_router,
updated_router_db, ha_settings_db,
router_requested, expire=True)
else:
# Notify redundancy routers about changes
self.notify_routers_updated(e_context, rr_ids)
elif gateway_changed is True:
# HA currently enabled (and to remain so) nor any HA setting update
# and gateway has changed
self._change_ha_for_gateway(e_context, updated_router,
updated_router_db, ha_settings_db,
router_requested)
# pick up updates to other attributes where it makes sense
# and push - right now it is only admin_state_up.
other_updates_spec = {'router': {}}
if 'admin_state_up' in update_specification['router']:
other_updates_spec['router']['admin_state_up'] = (
update_specification['router']['admin_state_up'])
if 'name' in update_specification['router']:
other_updates_spec['router']['name'] = (
update_specification['router']['name'])
if (other_updates_spec['router'] or
'routes' in update_specification['router']):
self._process_other_router_updates(e_context, updated_router_db,
other_updates_spec)
# Ensure we get latest state from DB
context.session.expire(updated_router_db)
self._extend_router_dict_ha(updated_router, updated_router_db) | python | def _update_redundancy_routers(self, context, updated_router,
update_specification, requested_ha_settings,
updated_router_db, gateway_changed):
"""To be called in update_router() AFTER router has been
updated in DB.
"""
router_requested = update_specification['router']
ha_settings_db = updated_router_db.ha_settings
ha_enabled_requested = requested_ha_settings.get(ha.ENABLED, False)
if not (updated_router[ha.ENABLED] or ha_enabled_requested):
# No HA currently enabled and no HA requested so we're done
return
# The redundancy routers need interfaces on the same networks as the
# user visible router.
ports = self._get_router_interfaces(updated_router_db)
e_context = context.elevated()
if not updated_router[ha.ENABLED] and ha_enabled_requested:
# No HA currently enabled but HA requested
router_requested.update(requested_ha_settings)
router_requested[EXTERNAL_GW_INFO] = (
updated_router[EXTERNAL_GW_INFO])
requested_ha_settings = self._ensure_create_ha_compliant(
router_requested, updated_router_db.hosting_info.router_type)
self._create_redundancy_routers(
e_context, updated_router, requested_ha_settings,
updated_router_db, ports, expire_db=True)
return
rr_ids = self._get_redundancy_router_ids(context, updated_router['id'])
ha_details_update_spec = requested_ha_settings.get(ha.DETAILS)
if (updated_router[ha.ENABLED] and not requested_ha_settings.get(
ha.ENABLED, updated_router[ha.ENABLED])):
# HA currently enabled but HA disable requested
# delete ha settings and extra port for gateway (VIP) port
self._delete_ha_group(e_context, updated_router_db.gw_port_id)
self._remove_redundancy_routers(e_context, rr_ids, ports, True)
with context.session.begin(subtransactions=True):
context.session.delete(ha_settings_db)
elif ha_details_update_spec:
# HA currently enabled and HA setting update (other than
# disable HA) requested
old_redundancy_level = ha_settings_db.redundancy_level
ha_settings_db.update(ha_details_update_spec)
diff = (ha_details_update_spec.get(ha.REDUNDANCY_LEVEL,
old_redundancy_level) -
old_redundancy_level)
with context.session.begin(subtransactions=True):
context.session.add(ha_settings_db)
if diff < 0:
# Remove -diff redundancy routers
#TODO(bobmel): Ensure currently active router is excluded
to_remove = rr_ids[len(rr_ids) + diff:]
rr_ids = rr_ids[:len(rr_ids) + diff]
self._remove_redundancy_routers(e_context, to_remove, ports)
elif diff > 0:
# Add diff redundancy routers
start = old_redundancy_level + 1
stop = start + diff
self._add_redundancy_routers(e_context, start, stop,
updated_router, ports,
ha_settings_db, False)
if gateway_changed is True:
self._change_ha_for_gateway(e_context, updated_router,
updated_router_db, ha_settings_db,
router_requested, expire=True)
else:
# Notify redundancy routers about changes
self.notify_routers_updated(e_context, rr_ids)
elif gateway_changed is True:
# HA currently enabled (and to remain so) nor any HA setting update
# and gateway has changed
self._change_ha_for_gateway(e_context, updated_router,
updated_router_db, ha_settings_db,
router_requested)
# pick up updates to other attributes where it makes sense
# and push - right now it is only admin_state_up.
other_updates_spec = {'router': {}}
if 'admin_state_up' in update_specification['router']:
other_updates_spec['router']['admin_state_up'] = (
update_specification['router']['admin_state_up'])
if 'name' in update_specification['router']:
other_updates_spec['router']['name'] = (
update_specification['router']['name'])
if (other_updates_spec['router'] or
'routes' in update_specification['router']):
self._process_other_router_updates(e_context, updated_router_db,
other_updates_spec)
# Ensure we get latest state from DB
context.session.expire(updated_router_db)
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updated in DB. | ['To', 'be', 'called', 'in', 'update_router', '()', 'AFTER', 'router', 'has', 'been', 'updated', 'in', 'DB', '.'] | train | https://github.com/openstack/networking-cisco/blob/aa58a30aec25b86f9aa5952b0863045975debfa9/networking_cisco/plugins/cisco/db/l3/ha_db.py#L336-L425 |
6,279 | HewlettPackard/python-hpOneView | hpOneView/resources/networking/ethernet_networks.py | EthernetNetworks.get_associated_uplink_groups | def get_associated_uplink_groups(self):
"""
Gets the uplink sets which are using an Ethernet network.
Returns:
list: URIs of the associated uplink sets.
"""
uri = "{}/associatedUplinkGroups".format(self.data['uri'])
return self._helper.do_get(uri) | python | def get_associated_uplink_groups(self):
"""
Gets the uplink sets which are using an Ethernet network.
Returns:
list: URIs of the associated uplink sets.
"""
uri = "{}/associatedUplinkGroups".format(self.data['uri'])
return self._helper.do_get(uri) | ['def', 'get_associated_uplink_groups', '(', 'self', ')', ':', 'uri', '=', '"{}/associatedUplinkGroups"', '.', 'format', '(', 'self', '.', 'data', '[', "'uri'", ']', ')', 'return', 'self', '.', '_helper', '.', 'do_get', '(', 'uri', ')'] | Gets the uplink sets which are using an Ethernet network.
Returns:
list: URIs of the associated uplink sets. | ['Gets', 'the', 'uplink', 'sets', 'which', 'are', 'using', 'an', 'Ethernet', 'network', '.'] | train | https://github.com/HewlettPackard/python-hpOneView/blob/3c6219723ef25e6e0c83d44a89007f89bc325b89/hpOneView/resources/networking/ethernet_networks.py#L169-L178 |
6,280 | boriel/zxbasic | arch/zx48k/optimizer.py | BasicBlock.get_first_non_label_instruction | def get_first_non_label_instruction(self):
""" Returns the memcell of the given block, which is
not a LABEL.
"""
for i in range(len(self)):
if not self.mem[i].is_label:
return self.mem[i]
return None | python | def get_first_non_label_instruction(self):
""" Returns the memcell of the given block, which is
not a LABEL.
"""
for i in range(len(self)):
if not self.mem[i].is_label:
return self.mem[i]
return None | ['def', 'get_first_non_label_instruction', '(', 'self', ')', ':', 'for', 'i', 'in', 'range', '(', 'len', '(', 'self', ')', ')', ':', 'if', 'not', 'self', '.', 'mem', '[', 'i', ']', '.', 'is_label', ':', 'return', 'self', '.', 'mem', '[', 'i', ']', 'return', 'None'] | Returns the memcell of the given block, which is
not a LABEL. | ['Returns', 'the', 'memcell', 'of', 'the', 'given', 'block', 'which', 'is', 'not', 'a', 'LABEL', '.'] | train | https://github.com/boriel/zxbasic/blob/23b28db10e41117805bdb3c0f78543590853b132/arch/zx48k/optimizer.py#L1664-L1672 |
6,281 | log2timeline/dfvfs | dfvfs/vfs/os_file_entry.py | OSDirectory._EntriesGenerator | def _EntriesGenerator(self):
"""Retrieves directory entries.
Since a directory can contain a vast number of entries using
a generator is more memory efficient.
Yields:
OSPathSpec: a path specification.
Raises:
AccessError: if the access to list the directory was denied.
BackEndError: if the directory could not be listed.
"""
location = getattr(self.path_spec, 'location', None)
if location is not None:
# Windows will raise WindowsError, which can be caught by OSError,
# if the process has not access to list the directory. The os.access()
# function cannot be used since it will return true even when os.listdir()
# fails.
try:
for directory_entry in os.listdir(location):
directory_entry_location = self._file_system.JoinPath([
location, directory_entry])
yield os_path_spec.OSPathSpec(location=directory_entry_location)
except OSError as exception:
if exception.errno == errno.EACCES:
exception_string = str(exception)
if not isinstance(exception_string, py2to3.UNICODE_TYPE):
exception_string = py2to3.UNICODE_TYPE(
exception_string, errors='replace')
raise errors.AccessError(
'Access to directory denied with error: {0!s}'.format(
exception_string))
else:
raise errors.BackEndError(
'Unable to list directory: {0:s} with error: {1!s}'.format(
location, exception)) | python | def _EntriesGenerator(self):
"""Retrieves directory entries.
Since a directory can contain a vast number of entries using
a generator is more memory efficient.
Yields:
OSPathSpec: a path specification.
Raises:
AccessError: if the access to list the directory was denied.
BackEndError: if the directory could not be listed.
"""
location = getattr(self.path_spec, 'location', None)
if location is not None:
# Windows will raise WindowsError, which can be caught by OSError,
# if the process has not access to list the directory. The os.access()
# function cannot be used since it will return true even when os.listdir()
# fails.
try:
for directory_entry in os.listdir(location):
directory_entry_location = self._file_system.JoinPath([
location, directory_entry])
yield os_path_spec.OSPathSpec(location=directory_entry_location)
except OSError as exception:
if exception.errno == errno.EACCES:
exception_string = str(exception)
if not isinstance(exception_string, py2to3.UNICODE_TYPE):
exception_string = py2to3.UNICODE_TYPE(
exception_string, errors='replace')
raise errors.AccessError(
'Access to directory denied with error: {0!s}'.format(
exception_string))
else:
raise errors.BackEndError(
'Unable to list directory: {0:s} with error: {1!s}'.format(
location, exception)) | ['def', '_EntriesGenerator', '(', 'self', ')', ':', 'location', '=', 'getattr', '(', 'self', '.', 'path_spec', ',', "'location'", ',', 'None', ')', 'if', 'location', 'is', 'not', 'None', ':', '# Windows will raise WindowsError, which can be caught by OSError,', '# if the process has not access to list the directory. The os.access()', '# function cannot be used since it will return true even when os.listdir()', '# fails.', 'try', ':', 'for', 'directory_entry', 'in', 'os', '.', 'listdir', '(', 'location', ')', ':', 'directory_entry_location', '=', 'self', '.', '_file_system', '.', 'JoinPath', '(', '[', 'location', ',', 'directory_entry', ']', ')', 'yield', 'os_path_spec', '.', 'OSPathSpec', '(', 'location', '=', 'directory_entry_location', ')', 'except', 'OSError', 'as', 'exception', ':', 'if', 'exception', '.', 'errno', '==', 'errno', '.', 'EACCES', ':', 'exception_string', '=', 'str', '(', 'exception', ')', 'if', 'not', 'isinstance', '(', 'exception_string', ',', 'py2to3', '.', 'UNICODE_TYPE', ')', ':', 'exception_string', '=', 'py2to3', '.', 'UNICODE_TYPE', '(', 'exception_string', ',', 'errors', '=', "'replace'", ')', 'raise', 'errors', '.', 'AccessError', '(', "'Access to directory denied with error: {0!s}'", '.', 'format', '(', 'exception_string', ')', ')', 'else', ':', 'raise', 'errors', '.', 'BackEndError', '(', "'Unable to list directory: {0:s} with error: {1!s}'", '.', 'format', '(', 'location', ',', 'exception', ')', ')'] | Retrieves directory entries.
Since a directory can contain a vast number of entries using
a generator is more memory efficient.
Yields:
OSPathSpec: a path specification.
Raises:
AccessError: if the access to list the directory was denied.
BackEndError: if the directory could not be listed. | ['Retrieves', 'directory', 'entries', '.'] | train | https://github.com/log2timeline/dfvfs/blob/2b3ccd115f9901d89f383397d4a1376a873c83c4/dfvfs/vfs/os_file_entry.py#L25-L63 |
6,282 | SuperCowPowers/workbench | workbench/workers/meta.py | MetaData.execute | def execute(self, input_data):
''' This worker computes meta data for any file type. '''
raw_bytes = input_data['sample']['raw_bytes']
self.meta['md5'] = hashlib.md5(raw_bytes).hexdigest()
self.meta['tags'] = input_data['tags']['tags']
self.meta['type_tag'] = input_data['sample']['type_tag']
with magic.Magic() as mag:
self.meta['file_type'] = mag.id_buffer(raw_bytes[:1024])
with magic.Magic(flags=magic.MAGIC_MIME_TYPE) as mag:
self.meta['mime_type'] = mag.id_buffer(raw_bytes[:1024])
with magic.Magic(flags=magic.MAGIC_MIME_ENCODING) as mag:
try:
self.meta['encoding'] = mag.id_buffer(raw_bytes[:1024])
except magic.MagicError:
self.meta['encoding'] = 'unknown'
self.meta['file_size'] = len(raw_bytes)
self.meta['filename'] = input_data['sample']['filename']
self.meta['import_time'] = input_data['sample']['import_time']
self.meta['customer'] = input_data['sample']['customer']
self.meta['length'] = input_data['sample']['length']
return self.meta | python | def execute(self, input_data):
''' This worker computes meta data for any file type. '''
raw_bytes = input_data['sample']['raw_bytes']
self.meta['md5'] = hashlib.md5(raw_bytes).hexdigest()
self.meta['tags'] = input_data['tags']['tags']
self.meta['type_tag'] = input_data['sample']['type_tag']
with magic.Magic() as mag:
self.meta['file_type'] = mag.id_buffer(raw_bytes[:1024])
with magic.Magic(flags=magic.MAGIC_MIME_TYPE) as mag:
self.meta['mime_type'] = mag.id_buffer(raw_bytes[:1024])
with magic.Magic(flags=magic.MAGIC_MIME_ENCODING) as mag:
try:
self.meta['encoding'] = mag.id_buffer(raw_bytes[:1024])
except magic.MagicError:
self.meta['encoding'] = 'unknown'
self.meta['file_size'] = len(raw_bytes)
self.meta['filename'] = input_data['sample']['filename']
self.meta['import_time'] = input_data['sample']['import_time']
self.meta['customer'] = input_data['sample']['customer']
self.meta['length'] = input_data['sample']['length']
return self.meta | ['def', 'execute', '(', 'self', ',', 'input_data', ')', ':', 'raw_bytes', '=', 'input_data', '[', "'sample'", ']', '[', "'raw_bytes'", ']', 'self', '.', 'meta', '[', "'md5'", ']', '=', 'hashlib', '.', 'md5', '(', 'raw_bytes', ')', '.', 'hexdigest', '(', ')', 'self', '.', 'meta', '[', "'tags'", ']', '=', 'input_data', '[', "'tags'", ']', '[', "'tags'", ']', 'self', '.', 'meta', '[', "'type_tag'", ']', '=', 'input_data', '[', "'sample'", ']', '[', "'type_tag'", ']', 'with', 'magic', '.', 'Magic', '(', ')', 'as', 'mag', ':', 'self', '.', 'meta', '[', "'file_type'", ']', '=', 'mag', '.', 'id_buffer', '(', 'raw_bytes', '[', ':', '1024', ']', ')', 'with', 'magic', '.', 'Magic', '(', 'flags', '=', 'magic', '.', 'MAGIC_MIME_TYPE', ')', 'as', 'mag', ':', 'self', '.', 'meta', '[', "'mime_type'", ']', '=', 'mag', '.', 'id_buffer', '(', 'raw_bytes', '[', ':', '1024', ']', ')', 'with', 'magic', '.', 'Magic', '(', 'flags', '=', 'magic', '.', 'MAGIC_MIME_ENCODING', ')', 'as', 'mag', ':', 'try', ':', 'self', '.', 'meta', '[', "'encoding'", ']', '=', 'mag', '.', 'id_buffer', '(', 'raw_bytes', '[', ':', '1024', ']', ')', 'except', 'magic', '.', 'MagicError', ':', 'self', '.', 'meta', '[', "'encoding'", ']', '=', "'unknown'", 'self', '.', 'meta', '[', "'file_size'", ']', '=', 'len', '(', 'raw_bytes', ')', 'self', '.', 'meta', '[', "'filename'", ']', '=', 'input_data', '[', "'sample'", ']', '[', "'filename'", ']', 'self', '.', 'meta', '[', "'import_time'", ']', '=', 'input_data', '[', "'sample'", ']', '[', "'import_time'", ']', 'self', '.', 'meta', '[', "'customer'", ']', '=', 'input_data', '[', "'sample'", ']', '[', "'customer'", ']', 'self', '.', 'meta', '[', "'length'", ']', '=', 'input_data', '[', "'sample'", ']', '[', "'length'", ']', 'return', 'self', '.', 'meta'] | This worker computes meta data for any file type. | ['This', 'worker', 'computes', 'meta', 'data', 'for', 'any', 'file', 'type', '.'] | train | https://github.com/SuperCowPowers/workbench/blob/710232756dd717f734253315e3d0b33c9628dafb/workbench/workers/meta.py#L15-L36 |
6,283 | geophysics-ubonn/reda | lib/reda/eis/plots.py | sip_response.plot | def plot(self, filename, title=None, reciprocal=None, limits=None,
dtype='rho', return_fig=False, **kwargs):
"""Standard plot of spectrum
Parameters
----------
filename: string
Output filename. Include the ending to specify the filetype
(usually .pdf or .png)
title: string, optional
Title for the plot
reciprocal: :class:`reda.eis.plots.sip_response`, optional
If another :class:`reda.eis.plots.sip_response` object is provided
here, use this as the reciprocal spectrum.
limits: dict, optional
A dictionary which contains plot limits. See code example below.
dtype: string, optional
Determines if the data plotted included geometric factors ('rho')
or not ('r'). Default: 'rho'
return_fig: bool, optional
If True, then do not delete the figure object after saving to file
and return the figure object. Default: False
**kwargs: dict
kwargs is piped through to the _plot function
Returns
-------
fig: :class:`matplotlib.Figure`
The figure object. Only returned if return_fig is set to True
Examples
--------
>>> from reda.eis.plots import sip_response
>>> import numpy as np
>>> frequencies = np.array([
... 1.00000000e-03, 1.77827941e-03, 3.16227766e-03, 5.62341325e-03,
... 1.00000000e-02, 1.77827941e-02, 3.16227766e-02, 5.62341325e-02,
... 1.00000000e-01, 1.77827941e-01, 3.16227766e-01, 5.62341325e-01,
... 1.00000000e+00, 1.77827941e+00, 3.16227766e+00, 5.62341325e+00,
... 1.00000000e+01, 1.77827941e+01, 3.16227766e+01, 5.62341325e+01,
... 1.00000000e+02, 1.77827941e+02, 3.16227766e+02, 5.62341325e+02,
... 1.00000000e+03])
>>> rcomplex = np.array([
... 49.34369772-0.51828971j, 49.11781581-0.59248806j,
... 48.85819872-0.6331137j , 48.58762806-0.62835135j,
... 48.33331113-0.57965851j, 48.11599009-0.50083533j,
... 47.94405036-0.41005275j, 47.81528917-0.32210768j,
... 47.72215469-0.24543425j, 47.65607773-0.18297794j,
... 47.60962191-0.13433101j, 47.57706229-0.09755774j,
... 47.55424286-0.07031682j, 47.53822912-0.05041399j,
... 47.52697253-0.03601005j, 47.51904718-0.02565412j,
... 47.51345965-0.01824266j, 47.50951606-0.01295546j,
... 47.50673042-0.00919217j, 47.50476152-0.0065178j ,
... 47.50336925-0.00461938j, 47.50238442-0.00327285j,
... 47.50168762-0.00231829j, 47.50119454-0.00164187j,
... 47.50084556-0.00116268j])
>>> spectrum = sip_response(frequencies=frequencies, rcomplex=rcomplex)
>>> fig = spectrum.plot('spectrum.pdf', return_fig=True)
"""
fig, axes = self._plot(
reciprocal=reciprocal,
limits=limits,
title=title,
dtype=dtype,
**kwargs
)
fig.savefig(filename, dpi=300)
if return_fig:
return fig
else:
plt.close(fig) | python | def plot(self, filename, title=None, reciprocal=None, limits=None,
dtype='rho', return_fig=False, **kwargs):
"""Standard plot of spectrum
Parameters
----------
filename: string
Output filename. Include the ending to specify the filetype
(usually .pdf or .png)
title: string, optional
Title for the plot
reciprocal: :class:`reda.eis.plots.sip_response`, optional
If another :class:`reda.eis.plots.sip_response` object is provided
here, use this as the reciprocal spectrum.
limits: dict, optional
A dictionary which contains plot limits. See code example below.
dtype: string, optional
Determines if the data plotted included geometric factors ('rho')
or not ('r'). Default: 'rho'
return_fig: bool, optional
If True, then do not delete the figure object after saving to file
and return the figure object. Default: False
**kwargs: dict
kwargs is piped through to the _plot function
Returns
-------
fig: :class:`matplotlib.Figure`
The figure object. Only returned if return_fig is set to True
Examples
--------
>>> from reda.eis.plots import sip_response
>>> import numpy as np
>>> frequencies = np.array([
... 1.00000000e-03, 1.77827941e-03, 3.16227766e-03, 5.62341325e-03,
... 1.00000000e-02, 1.77827941e-02, 3.16227766e-02, 5.62341325e-02,
... 1.00000000e-01, 1.77827941e-01, 3.16227766e-01, 5.62341325e-01,
... 1.00000000e+00, 1.77827941e+00, 3.16227766e+00, 5.62341325e+00,
... 1.00000000e+01, 1.77827941e+01, 3.16227766e+01, 5.62341325e+01,
... 1.00000000e+02, 1.77827941e+02, 3.16227766e+02, 5.62341325e+02,
... 1.00000000e+03])
>>> rcomplex = np.array([
... 49.34369772-0.51828971j, 49.11781581-0.59248806j,
... 48.85819872-0.6331137j , 48.58762806-0.62835135j,
... 48.33331113-0.57965851j, 48.11599009-0.50083533j,
... 47.94405036-0.41005275j, 47.81528917-0.32210768j,
... 47.72215469-0.24543425j, 47.65607773-0.18297794j,
... 47.60962191-0.13433101j, 47.57706229-0.09755774j,
... 47.55424286-0.07031682j, 47.53822912-0.05041399j,
... 47.52697253-0.03601005j, 47.51904718-0.02565412j,
... 47.51345965-0.01824266j, 47.50951606-0.01295546j,
... 47.50673042-0.00919217j, 47.50476152-0.0065178j ,
... 47.50336925-0.00461938j, 47.50238442-0.00327285j,
... 47.50168762-0.00231829j, 47.50119454-0.00164187j,
... 47.50084556-0.00116268j])
>>> spectrum = sip_response(frequencies=frequencies, rcomplex=rcomplex)
>>> fig = spectrum.plot('spectrum.pdf', return_fig=True)
"""
fig, axes = self._plot(
reciprocal=reciprocal,
limits=limits,
title=title,
dtype=dtype,
**kwargs
)
fig.savefig(filename, dpi=300)
if return_fig:
return fig
else:
plt.close(fig) | ['def', 'plot', '(', 'self', ',', 'filename', ',', 'title', '=', 'None', ',', 'reciprocal', '=', 'None', ',', 'limits', '=', 'None', ',', 'dtype', '=', "'rho'", ',', 'return_fig', '=', 'False', ',', '*', '*', 'kwargs', ')', ':', 'fig', ',', 'axes', '=', 'self', '.', '_plot', '(', 'reciprocal', '=', 'reciprocal', ',', 'limits', '=', 'limits', ',', 'title', '=', 'title', ',', 'dtype', '=', 'dtype', ',', '*', '*', 'kwargs', ')', 'fig', '.', 'savefig', '(', 'filename', ',', 'dpi', '=', '300', ')', 'if', 'return_fig', ':', 'return', 'fig', 'else', ':', 'plt', '.', 'close', '(', 'fig', ')'] | Standard plot of spectrum
Parameters
----------
filename: string
Output filename. Include the ending to specify the filetype
(usually .pdf or .png)
title: string, optional
Title for the plot
reciprocal: :class:`reda.eis.plots.sip_response`, optional
If another :class:`reda.eis.plots.sip_response` object is provided
here, use this as the reciprocal spectrum.
limits: dict, optional
A dictionary which contains plot limits. See code example below.
dtype: string, optional
Determines if the data plotted included geometric factors ('rho')
or not ('r'). Default: 'rho'
return_fig: bool, optional
If True, then do not delete the figure object after saving to file
and return the figure object. Default: False
**kwargs: dict
kwargs is piped through to the _plot function
Returns
-------
fig: :class:`matplotlib.Figure`
The figure object. Only returned if return_fig is set to True
Examples
--------
>>> from reda.eis.plots import sip_response
>>> import numpy as np
>>> frequencies = np.array([
... 1.00000000e-03, 1.77827941e-03, 3.16227766e-03, 5.62341325e-03,
... 1.00000000e-02, 1.77827941e-02, 3.16227766e-02, 5.62341325e-02,
... 1.00000000e-01, 1.77827941e-01, 3.16227766e-01, 5.62341325e-01,
... 1.00000000e+00, 1.77827941e+00, 3.16227766e+00, 5.62341325e+00,
... 1.00000000e+01, 1.77827941e+01, 3.16227766e+01, 5.62341325e+01,
... 1.00000000e+02, 1.77827941e+02, 3.16227766e+02, 5.62341325e+02,
... 1.00000000e+03])
>>> rcomplex = np.array([
... 49.34369772-0.51828971j, 49.11781581-0.59248806j,
... 48.85819872-0.6331137j , 48.58762806-0.62835135j,
... 48.33331113-0.57965851j, 48.11599009-0.50083533j,
... 47.94405036-0.41005275j, 47.81528917-0.32210768j,
... 47.72215469-0.24543425j, 47.65607773-0.18297794j,
... 47.60962191-0.13433101j, 47.57706229-0.09755774j,
... 47.55424286-0.07031682j, 47.53822912-0.05041399j,
... 47.52697253-0.03601005j, 47.51904718-0.02565412j,
... 47.51345965-0.01824266j, 47.50951606-0.01295546j,
... 47.50673042-0.00919217j, 47.50476152-0.0065178j ,
... 47.50336925-0.00461938j, 47.50238442-0.00327285j,
... 47.50168762-0.00231829j, 47.50119454-0.00164187j,
... 47.50084556-0.00116268j])
>>> spectrum = sip_response(frequencies=frequencies, rcomplex=rcomplex)
>>> fig = spectrum.plot('spectrum.pdf', return_fig=True) | ['Standard', 'plot', 'of', 'spectrum'] | train | https://github.com/geophysics-ubonn/reda/blob/46a939729e40c7c4723315c03679c40761152e9e/lib/reda/eis/plots.py#L250-L321 |
6,284 | theislab/anndata | anndata/base.py | _gen_keys_from_multicol_key | def _gen_keys_from_multicol_key(key_multicol, n_keys):
"""Generates single-column keys from multicolumn key."""
keys = [('{}{:03}of{:03}')
.format(key_multicol, i+1, n_keys) for i in range(n_keys)]
return keys | python | def _gen_keys_from_multicol_key(key_multicol, n_keys):
"""Generates single-column keys from multicolumn key."""
keys = [('{}{:03}of{:03}')
.format(key_multicol, i+1, n_keys) for i in range(n_keys)]
return keys | ['def', '_gen_keys_from_multicol_key', '(', 'key_multicol', ',', 'n_keys', ')', ':', 'keys', '=', '[', '(', "'{}{:03}of{:03}'", ')', '.', 'format', '(', 'key_multicol', ',', 'i', '+', '1', ',', 'n_keys', ')', 'for', 'i', 'in', 'range', '(', 'n_keys', ')', ']', 'return', 'keys'] | Generates single-column keys from multicolumn key. | ['Generates', 'single', '-', 'column', 'keys', 'from', 'multicolumn', 'key', '.'] | train | https://github.com/theislab/anndata/blob/34f4eb63710628fbc15e7050e5efcac1d7806062/anndata/base.py#L186-L190 |
6,285 | singularityhub/singularity-cli | spython/main/execute.py | execute | def execute(self,
image = None,
command = None,
app = None,
writable = False,
contain = False,
bind = None,
stream = False,
nv = False,
return_result=False):
''' execute: send a command to a container
Parameters
==========
image: full path to singularity image
command: command to send to container
app: if not None, execute a command in context of an app
writable: This option makes the file system accessible as read/write
contain: This option disables the automatic sharing of writable
filesystems on your host
bind: list or single string of bind paths.
This option allows you to map directories on your host system to
directories within your container using bind mounts
nv: if True, load Nvidia Drivers in runtime (default False)
return_result: if True, return entire json object with return code
and message result (default is False)
'''
from spython.utils import check_install
check_install()
cmd = self._init_command('exec')
# nv option leverages any GPU cards
if nv is True:
cmd += ['--nv']
# If the image is given as a list, it's probably the command
if isinstance(image, list):
command = image
image = None
if command is not None:
# No image provided, default to use the client's loaded image
if image is None:
image = self._get_uri()
self.quiet = True
# If an instance is provided, grab it's name
if isinstance(image, self.instance):
image = image.get_uri()
# Does the user want to use bind paths option?
if bind is not None:
cmd += self._generate_bind_list(bind)
# Does the user want to run an app?
if app is not None:
cmd = cmd + ['--app', app]
sudo = False
if writable is True:
sudo = True
if not isinstance(command, list):
command = command.split(' ')
cmd = cmd + [image] + command
if stream is False:
return self._run_command(cmd,
sudo=sudo,
return_result=return_result)
return stream_command(cmd, sudo=sudo)
bot.error('Please include a command (list) to execute.') | python | def execute(self,
image = None,
command = None,
app = None,
writable = False,
contain = False,
bind = None,
stream = False,
nv = False,
return_result=False):
''' execute: send a command to a container
Parameters
==========
image: full path to singularity image
command: command to send to container
app: if not None, execute a command in context of an app
writable: This option makes the file system accessible as read/write
contain: This option disables the automatic sharing of writable
filesystems on your host
bind: list or single string of bind paths.
This option allows you to map directories on your host system to
directories within your container using bind mounts
nv: if True, load Nvidia Drivers in runtime (default False)
return_result: if True, return entire json object with return code
and message result (default is False)
'''
from spython.utils import check_install
check_install()
cmd = self._init_command('exec')
# nv option leverages any GPU cards
if nv is True:
cmd += ['--nv']
# If the image is given as a list, it's probably the command
if isinstance(image, list):
command = image
image = None
if command is not None:
# No image provided, default to use the client's loaded image
if image is None:
image = self._get_uri()
self.quiet = True
# If an instance is provided, grab it's name
if isinstance(image, self.instance):
image = image.get_uri()
# Does the user want to use bind paths option?
if bind is not None:
cmd += self._generate_bind_list(bind)
# Does the user want to run an app?
if app is not None:
cmd = cmd + ['--app', app]
sudo = False
if writable is True:
sudo = True
if not isinstance(command, list):
command = command.split(' ')
cmd = cmd + [image] + command
if stream is False:
return self._run_command(cmd,
sudo=sudo,
return_result=return_result)
return stream_command(cmd, sudo=sudo)
bot.error('Please include a command (list) to execute.') | ['def', 'execute', '(', 'self', ',', 'image', '=', 'None', ',', 'command', '=', 'None', ',', 'app', '=', 'None', ',', 'writable', '=', 'False', ',', 'contain', '=', 'False', ',', 'bind', '=', 'None', ',', 'stream', '=', 'False', ',', 'nv', '=', 'False', ',', 'return_result', '=', 'False', ')', ':', 'from', 'spython', '.', 'utils', 'import', 'check_install', 'check_install', '(', ')', 'cmd', '=', 'self', '.', '_init_command', '(', "'exec'", ')', '# nv option leverages any GPU cards', 'if', 'nv', 'is', 'True', ':', 'cmd', '+=', '[', "'--nv'", ']', "# If the image is given as a list, it's probably the command", 'if', 'isinstance', '(', 'image', ',', 'list', ')', ':', 'command', '=', 'image', 'image', '=', 'None', 'if', 'command', 'is', 'not', 'None', ':', "# No image provided, default to use the client's loaded image", 'if', 'image', 'is', 'None', ':', 'image', '=', 'self', '.', '_get_uri', '(', ')', 'self', '.', 'quiet', '=', 'True', "# If an instance is provided, grab it's name", 'if', 'isinstance', '(', 'image', ',', 'self', '.', 'instance', ')', ':', 'image', '=', 'image', '.', 'get_uri', '(', ')', '# Does the user want to use bind paths option?', 'if', 'bind', 'is', 'not', 'None', ':', 'cmd', '+=', 'self', '.', '_generate_bind_list', '(', 'bind', ')', '# Does the user want to run an app?', 'if', 'app', 'is', 'not', 'None', ':', 'cmd', '=', 'cmd', '+', '[', "'--app'", ',', 'app', ']', 'sudo', '=', 'False', 'if', 'writable', 'is', 'True', ':', 'sudo', '=', 'True', 'if', 'not', 'isinstance', '(', 'command', ',', 'list', ')', ':', 'command', '=', 'command', '.', 'split', '(', "' '", ')', 'cmd', '=', 'cmd', '+', '[', 'image', ']', '+', 'command', 'if', 'stream', 'is', 'False', ':', 'return', 'self', '.', '_run_command', '(', 'cmd', ',', 'sudo', '=', 'sudo', ',', 'return_result', '=', 'return_result', ')', 'return', 'stream_command', '(', 'cmd', ',', 'sudo', '=', 'sudo', ')', 'bot', '.', 'error', '(', "'Please include a command (list) to execute.'", ')'] | execute: send a command to a container
Parameters
==========
image: full path to singularity image
command: command to send to container
app: if not None, execute a command in context of an app
writable: This option makes the file system accessible as read/write
contain: This option disables the automatic sharing of writable
filesystems on your host
bind: list or single string of bind paths.
This option allows you to map directories on your host system to
directories within your container using bind mounts
nv: if True, load Nvidia Drivers in runtime (default False)
return_result: if True, return entire json object with return code
and message result (default is False) | ['execute', ':', 'send', 'a', 'command', 'to', 'a', 'container', 'Parameters', '=========='] | train | https://github.com/singularityhub/singularity-cli/blob/cb36b4504812ca87e29c6a40b222a545d1865799/spython/main/execute.py#L15-L92 |
6,286 | mapbox/mapbox-sdk-py | mapbox/services/matrix.py | DirectionsMatrix.matrix | def matrix(self, coordinates, profile='mapbox/driving',
sources=None, destinations=None, annotations=None):
"""Request a directions matrix for trips between coordinates
In the default case, the matrix returns a symmetric matrix,
using all input coordinates as sources and destinations. You may
also generate an asymmetric matrix, with only some coordinates
as sources or destinations:
Parameters
----------
coordinates : sequence
A sequence of coordinates, which may be represented as
GeoJSON features, GeoJSON geometries, or (longitude,
latitude) pairs.
profile : str
The trip travel mode. Valid modes are listed in the class's
valid_profiles attribute.
annotations : list
Used to specify the resulting matrices. Possible values are
listed in the class's valid_annotations attribute.
sources : list
Indices of source coordinates to include in the matrix.
Default is all coordinates.
destinations : list
Indices of destination coordinates to include in the
matrix. Default is all coordinates.
Returns
-------
requests.Response
Note: the directions matrix itself is obtained by calling the
response's json() method. The resulting mapping has a code,
the destinations and the sources, and depending of the
annotations specified, it can also contain a durations matrix,
a distances matrix or both of them (by default, only the
durations matrix is provided).
code : str
Status of the response
sources : list
Results of snapping selected coordinates to the nearest
addresses.
destinations : list
Results of snapping selected coordinates to the nearest
addresses.
durations : list
An array of arrays representing the matrix in row-major
order. durations[i][j] gives the travel time from the i-th
source to the j-th destination. All values are in seconds.
The duration between the same coordinate is always 0. If
a duration can not be found, the result is null.
distances : list
An array of arrays representing the matrix in row-major
order. distances[i][j] gives the distance from the i-th
source to the j-th destination. All values are in meters.
The distance between the same coordinate is always 0. If
a distance can not be found, the result is null.
"""
annotations = self._validate_annotations(annotations)
profile = self._validate_profile(profile)
coords = encode_waypoints(coordinates)
params = self._make_query(sources, destinations)
if annotations is not None:
params.update({'annotations': ','.join(annotations)})
uri = '{0}/{1}/{2}'.format(self.baseuri, profile, coords)
res = self.session.get(uri, params=params)
self.handle_http_error(res)
return res | python | def matrix(self, coordinates, profile='mapbox/driving',
sources=None, destinations=None, annotations=None):
"""Request a directions matrix for trips between coordinates
In the default case, the matrix returns a symmetric matrix,
using all input coordinates as sources and destinations. You may
also generate an asymmetric matrix, with only some coordinates
as sources or destinations:
Parameters
----------
coordinates : sequence
A sequence of coordinates, which may be represented as
GeoJSON features, GeoJSON geometries, or (longitude,
latitude) pairs.
profile : str
The trip travel mode. Valid modes are listed in the class's
valid_profiles attribute.
annotations : list
Used to specify the resulting matrices. Possible values are
listed in the class's valid_annotations attribute.
sources : list
Indices of source coordinates to include in the matrix.
Default is all coordinates.
destinations : list
Indices of destination coordinates to include in the
matrix. Default is all coordinates.
Returns
-------
requests.Response
Note: the directions matrix itself is obtained by calling the
response's json() method. The resulting mapping has a code,
the destinations and the sources, and depending of the
annotations specified, it can also contain a durations matrix,
a distances matrix or both of them (by default, only the
durations matrix is provided).
code : str
Status of the response
sources : list
Results of snapping selected coordinates to the nearest
addresses.
destinations : list
Results of snapping selected coordinates to the nearest
addresses.
durations : list
An array of arrays representing the matrix in row-major
order. durations[i][j] gives the travel time from the i-th
source to the j-th destination. All values are in seconds.
The duration between the same coordinate is always 0. If
a duration can not be found, the result is null.
distances : list
An array of arrays representing the matrix in row-major
order. distances[i][j] gives the distance from the i-th
source to the j-th destination. All values are in meters.
The distance between the same coordinate is always 0. If
a distance can not be found, the result is null.
"""
annotations = self._validate_annotations(annotations)
profile = self._validate_profile(profile)
coords = encode_waypoints(coordinates)
params = self._make_query(sources, destinations)
if annotations is not None:
params.update({'annotations': ','.join(annotations)})
uri = '{0}/{1}/{2}'.format(self.baseuri, profile, coords)
res = self.session.get(uri, params=params)
self.handle_http_error(res)
return res | ['def', 'matrix', '(', 'self', ',', 'coordinates', ',', 'profile', '=', "'mapbox/driving'", ',', 'sources', '=', 'None', ',', 'destinations', '=', 'None', ',', 'annotations', '=', 'None', ')', ':', 'annotations', '=', 'self', '.', '_validate_annotations', '(', 'annotations', ')', 'profile', '=', 'self', '.', '_validate_profile', '(', 'profile', ')', 'coords', '=', 'encode_waypoints', '(', 'coordinates', ')', 'params', '=', 'self', '.', '_make_query', '(', 'sources', ',', 'destinations', ')', 'if', 'annotations', 'is', 'not', 'None', ':', 'params', '.', 'update', '(', '{', "'annotations'", ':', "','", '.', 'join', '(', 'annotations', ')', '}', ')', 'uri', '=', "'{0}/{1}/{2}'", '.', 'format', '(', 'self', '.', 'baseuri', ',', 'profile', ',', 'coords', ')', 'res', '=', 'self', '.', 'session', '.', 'get', '(', 'uri', ',', 'params', '=', 'params', ')', 'self', '.', 'handle_http_error', '(', 'res', ')', 'return', 'res'] | Request a directions matrix for trips between coordinates
In the default case, the matrix returns a symmetric matrix,
using all input coordinates as sources and destinations. You may
also generate an asymmetric matrix, with only some coordinates
as sources or destinations:
Parameters
----------
coordinates : sequence
A sequence of coordinates, which may be represented as
GeoJSON features, GeoJSON geometries, or (longitude,
latitude) pairs.
profile : str
The trip travel mode. Valid modes are listed in the class's
valid_profiles attribute.
annotations : list
Used to specify the resulting matrices. Possible values are
listed in the class's valid_annotations attribute.
sources : list
Indices of source coordinates to include in the matrix.
Default is all coordinates.
destinations : list
Indices of destination coordinates to include in the
matrix. Default is all coordinates.
Returns
-------
requests.Response
Note: the directions matrix itself is obtained by calling the
response's json() method. The resulting mapping has a code,
the destinations and the sources, and depending of the
annotations specified, it can also contain a durations matrix,
a distances matrix or both of them (by default, only the
durations matrix is provided).
code : str
Status of the response
sources : list
Results of snapping selected coordinates to the nearest
addresses.
destinations : list
Results of snapping selected coordinates to the nearest
addresses.
durations : list
An array of arrays representing the matrix in row-major
order. durations[i][j] gives the travel time from the i-th
source to the j-th destination. All values are in seconds.
The duration between the same coordinate is always 0. If
a duration can not be found, the result is null.
distances : list
An array of arrays representing the matrix in row-major
order. distances[i][j] gives the distance from the i-th
source to the j-th destination. All values are in meters.
The distance between the same coordinate is always 0. If
a distance can not be found, the result is null. | ['Request', 'a', 'directions', 'matrix', 'for', 'trips', 'between', 'coordinates'] | train | https://github.com/mapbox/mapbox-sdk-py/blob/72d19dbcf2d254a6ea08129a726471fd21f13023/mapbox/services/matrix.py#L65-L138 |
6,287 | Kopachris/seshet | seshet/config.py | build_bot | def build_bot(config_file=None):
"""Parse a config and return a SeshetBot instance. After, the bot can be run
simply by calling .connect() and then .start()
Optional arguments:
config_file - valid file path or ConfigParser instance
If config_file is None, will read default config defined in this module.
"""
from . import bot
config = ConfigParser(interpolation=None)
if config_file is None:
config.read_string(default_config)
elif isinstance(config_file, ConfigParser):
config = config_file
else:
config.read(config_file)
# shorter names
db_conf = config['database']
conn_conf = config['connection']
client_conf = config['client']
log_conf = config['logging']
verbosity = config['debug']['verbosity'].lower() or 'notset'
debug_file = config['debug']['file'] or None
# add more as they're used
if db_conf.getboolean('use_db'):
db = DAL(db_conf['db_string'])
build_db_tables(db)
log_file = None
log_fmts = {}
else:
db = None
log_file = log_conf.pop('file')
log_fmts = dict(log_conf)
# debug logging
debug_lvls = {'notset': 0,
'debug': 10,
'info': 20,
'warning': 30,
'error': 40,
'critical': 50,
}
lvl = int(debug_lvls[verbosity])
seshetbot = bot.SeshetBot(client_conf['nickname'], db, debug_file, lvl)
# connection info for connect()
seshetbot.default_host = conn_conf['server']
seshetbot.default_port = int(conn_conf['port'])
seshetbot.default_channel = conn_conf['channels'].split(',')
seshetbot.default_use_ssl = conn_conf.getboolean('ssl')
# client info
seshetbot.user = client_conf['user']
seshetbot.real_name = client_conf['realname']
# logging info
seshetbot.log_file = log_file
seshetbot.log_formats = log_fmts
seshetbot.locale = dict(config['locale'])
return seshetbot | python | def build_bot(config_file=None):
"""Parse a config and return a SeshetBot instance. After, the bot can be run
simply by calling .connect() and then .start()
Optional arguments:
config_file - valid file path or ConfigParser instance
If config_file is None, will read default config defined in this module.
"""
from . import bot
config = ConfigParser(interpolation=None)
if config_file is None:
config.read_string(default_config)
elif isinstance(config_file, ConfigParser):
config = config_file
else:
config.read(config_file)
# shorter names
db_conf = config['database']
conn_conf = config['connection']
client_conf = config['client']
log_conf = config['logging']
verbosity = config['debug']['verbosity'].lower() or 'notset'
debug_file = config['debug']['file'] or None
# add more as they're used
if db_conf.getboolean('use_db'):
db = DAL(db_conf['db_string'])
build_db_tables(db)
log_file = None
log_fmts = {}
else:
db = None
log_file = log_conf.pop('file')
log_fmts = dict(log_conf)
# debug logging
debug_lvls = {'notset': 0,
'debug': 10,
'info': 20,
'warning': 30,
'error': 40,
'critical': 50,
}
lvl = int(debug_lvls[verbosity])
seshetbot = bot.SeshetBot(client_conf['nickname'], db, debug_file, lvl)
# connection info for connect()
seshetbot.default_host = conn_conf['server']
seshetbot.default_port = int(conn_conf['port'])
seshetbot.default_channel = conn_conf['channels'].split(',')
seshetbot.default_use_ssl = conn_conf.getboolean('ssl')
# client info
seshetbot.user = client_conf['user']
seshetbot.real_name = client_conf['realname']
# logging info
seshetbot.log_file = log_file
seshetbot.log_formats = log_fmts
seshetbot.locale = dict(config['locale'])
return seshetbot | ['def', 'build_bot', '(', 'config_file', '=', 'None', ')', ':', 'from', '.', 'import', 'bot', 'config', '=', 'ConfigParser', '(', 'interpolation', '=', 'None', ')', 'if', 'config_file', 'is', 'None', ':', 'config', '.', 'read_string', '(', 'default_config', ')', 'elif', 'isinstance', '(', 'config_file', ',', 'ConfigParser', ')', ':', 'config', '=', 'config_file', 'else', ':', 'config', '.', 'read', '(', 'config_file', ')', '# shorter names', 'db_conf', '=', 'config', '[', "'database'", ']', 'conn_conf', '=', 'config', '[', "'connection'", ']', 'client_conf', '=', 'config', '[', "'client'", ']', 'log_conf', '=', 'config', '[', "'logging'", ']', 'verbosity', '=', 'config', '[', "'debug'", ']', '[', "'verbosity'", ']', '.', 'lower', '(', ')', 'or', "'notset'", 'debug_file', '=', 'config', '[', "'debug'", ']', '[', "'file'", ']', 'or', 'None', "# add more as they're used", 'if', 'db_conf', '.', 'getboolean', '(', "'use_db'", ')', ':', 'db', '=', 'DAL', '(', 'db_conf', '[', "'db_string'", ']', ')', 'build_db_tables', '(', 'db', ')', 'log_file', '=', 'None', 'log_fmts', '=', '{', '}', 'else', ':', 'db', '=', 'None', 'log_file', '=', 'log_conf', '.', 'pop', '(', "'file'", ')', 'log_fmts', '=', 'dict', '(', 'log_conf', ')', '# debug logging', 'debug_lvls', '=', '{', "'notset'", ':', '0', ',', "'debug'", ':', '10', ',', "'info'", ':', '20', ',', "'warning'", ':', '30', ',', "'error'", ':', '40', ',', "'critical'", ':', '50', ',', '}', 'lvl', '=', 'int', '(', 'debug_lvls', '[', 'verbosity', ']', ')', 'seshetbot', '=', 'bot', '.', 'SeshetBot', '(', 'client_conf', '[', "'nickname'", ']', ',', 'db', ',', 'debug_file', ',', 'lvl', ')', '# connection info for connect()', 'seshetbot', '.', 'default_host', '=', 'conn_conf', '[', "'server'", ']', 'seshetbot', '.', 'default_port', '=', 'int', '(', 'conn_conf', '[', "'port'", ']', ')', 'seshetbot', '.', 'default_channel', '=', 'conn_conf', '[', "'channels'", ']', '.', 'split', '(', "','", ')', 'seshetbot', '.', 'default_use_ssl', '=', 'conn_conf', '.', 'getboolean', '(', "'ssl'", ')', '# client info', 'seshetbot', '.', 'user', '=', 'client_conf', '[', "'user'", ']', 'seshetbot', '.', 'real_name', '=', 'client_conf', '[', "'realname'", ']', '# logging info', 'seshetbot', '.', 'log_file', '=', 'log_file', 'seshetbot', '.', 'log_formats', '=', 'log_fmts', 'seshetbot', '.', 'locale', '=', 'dict', '(', 'config', '[', "'locale'", ']', ')', 'return', 'seshetbot'] | Parse a config and return a SeshetBot instance. After, the bot can be run
simply by calling .connect() and then .start()
Optional arguments:
config_file - valid file path or ConfigParser instance
If config_file is None, will read default config defined in this module. | ['Parse', 'a', 'config', 'and', 'return', 'a', 'SeshetBot', 'instance', '.', 'After', 'the', 'bot', 'can', 'be', 'run', 'simply', 'by', 'calling', '.', 'connect', '()', 'and', 'then', '.', 'start', '()', 'Optional', 'arguments', ':', 'config_file', '-', 'valid', 'file', 'path', 'or', 'ConfigParser', 'instance', 'If', 'config_file', 'is', 'None', 'will', 'read', 'default', 'config', 'defined', 'in', 'this', 'module', '.'] | train | https://github.com/Kopachris/seshet/blob/d55bae01cff56762c5467138474145a2c17d1932/seshet/config.py#L156-L222 |
6,288 | Erotemic/utool | utool/util_list.py | scalar_input_map | def scalar_input_map(func, input_):
"""
Map like function
Args:
func: function to apply
input_ : either an iterable or scalar value
Returns:
If ``input_`` is iterable this function behaves like map
otherwise applies func to ``input_``
"""
if util_iter.isiterable(input_):
return list(map(func, input_))
else:
return func(input_) | python | def scalar_input_map(func, input_):
"""
Map like function
Args:
func: function to apply
input_ : either an iterable or scalar value
Returns:
If ``input_`` is iterable this function behaves like map
otherwise applies func to ``input_``
"""
if util_iter.isiterable(input_):
return list(map(func, input_))
else:
return func(input_) | ['def', 'scalar_input_map', '(', 'func', ',', 'input_', ')', ':', 'if', 'util_iter', '.', 'isiterable', '(', 'input_', ')', ':', 'return', 'list', '(', 'map', '(', 'func', ',', 'input_', ')', ')', 'else', ':', 'return', 'func', '(', 'input_', ')'] | Map like function
Args:
func: function to apply
input_ : either an iterable or scalar value
Returns:
If ``input_`` is iterable this function behaves like map
otherwise applies func to ``input_`` | ['Map', 'like', 'function'] | train | https://github.com/Erotemic/utool/blob/3b27e1f4e6e6fb23cd8744af7b7195b57d99e03a/utool/util_list.py#L2061-L2076 |
6,289 | GNS3/gns3-server | gns3server/compute/port_manager.py | PortManager._check_port | def _check_port(host, port, socket_type):
"""
Check if an a port is available and raise an OSError if port is not available
:returns: boolean
"""
if socket_type == "UDP":
socket_type = socket.SOCK_DGRAM
else:
socket_type = socket.SOCK_STREAM
for res in socket.getaddrinfo(host, port, socket.AF_UNSPEC, socket_type, 0, socket.AI_PASSIVE):
af, socktype, proto, _, sa = res
with socket.socket(af, socktype, proto) as s:
s.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
s.bind(sa) # the port is available if bind is a success
return True | python | def _check_port(host, port, socket_type):
"""
Check if an a port is available and raise an OSError if port is not available
:returns: boolean
"""
if socket_type == "UDP":
socket_type = socket.SOCK_DGRAM
else:
socket_type = socket.SOCK_STREAM
for res in socket.getaddrinfo(host, port, socket.AF_UNSPEC, socket_type, 0, socket.AI_PASSIVE):
af, socktype, proto, _, sa = res
with socket.socket(af, socktype, proto) as s:
s.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
s.bind(sa) # the port is available if bind is a success
return True | ['def', '_check_port', '(', 'host', ',', 'port', ',', 'socket_type', ')', ':', 'if', 'socket_type', '==', '"UDP"', ':', 'socket_type', '=', 'socket', '.', 'SOCK_DGRAM', 'else', ':', 'socket_type', '=', 'socket', '.', 'SOCK_STREAM', 'for', 'res', 'in', 'socket', '.', 'getaddrinfo', '(', 'host', ',', 'port', ',', 'socket', '.', 'AF_UNSPEC', ',', 'socket_type', ',', '0', ',', 'socket', '.', 'AI_PASSIVE', ')', ':', 'af', ',', 'socktype', ',', 'proto', ',', '_', ',', 'sa', '=', 'res', 'with', 'socket', '.', 'socket', '(', 'af', ',', 'socktype', ',', 'proto', ')', 'as', 's', ':', 's', '.', 'setsockopt', '(', 'socket', '.', 'SOL_SOCKET', ',', 'socket', '.', 'SO_REUSEADDR', ',', '1', ')', 's', '.', 'bind', '(', 'sa', ')', '# the port is available if bind is a success', 'return', 'True'] | Check if an a port is available and raise an OSError if port is not available
:returns: boolean | ['Check', 'if', 'an', 'a', 'port', 'is', 'available', 'and', 'raise', 'an', 'OSError', 'if', 'port', 'is', 'not', 'available'] | train | https://github.com/GNS3/gns3-server/blob/a221678448fb5d24e977ef562f81d56aacc89ab1/gns3server/compute/port_manager.py#L168-L184 |
6,290 | oauthlib/oauthlib | oauthlib/oauth1/rfc5849/__init__.py | Client.get_oauth_params | def get_oauth_params(self, request):
"""Get the basic OAuth parameters to be used in generating a signature.
"""
nonce = (generate_nonce()
if self.nonce is None else self.nonce)
timestamp = (generate_timestamp()
if self.timestamp is None else self.timestamp)
params = [
('oauth_nonce', nonce),
('oauth_timestamp', timestamp),
('oauth_version', '1.0'),
('oauth_signature_method', self.signature_method),
('oauth_consumer_key', self.client_key),
]
if self.resource_owner_key:
params.append(('oauth_token', self.resource_owner_key))
if self.callback_uri:
params.append(('oauth_callback', self.callback_uri))
if self.verifier:
params.append(('oauth_verifier', self.verifier))
# providing body hash for requests other than x-www-form-urlencoded
# as described in https://tools.ietf.org/html/draft-eaton-oauth-bodyhash-00#section-4.1.1
# 4.1.1. When to include the body hash
# * [...] MUST NOT include an oauth_body_hash parameter on requests with form-encoded request bodies
# * [...] SHOULD include the oauth_body_hash parameter on all other requests.
# Note that SHA-1 is vulnerable. The spec acknowledges that in https://tools.ietf.org/html/draft-eaton-oauth-bodyhash-00#section-6.2
# At this time, no further effort has been made to replace SHA-1 for the OAuth Request Body Hash extension.
content_type = request.headers.get('Content-Type', None)
content_type_eligible = content_type and content_type.find('application/x-www-form-urlencoded') < 0
if request.body is not None and content_type_eligible:
params.append(('oauth_body_hash', base64.b64encode(hashlib.sha1(request.body.encode('utf-8')).digest()).decode('utf-8')))
return params | python | def get_oauth_params(self, request):
"""Get the basic OAuth parameters to be used in generating a signature.
"""
nonce = (generate_nonce()
if self.nonce is None else self.nonce)
timestamp = (generate_timestamp()
if self.timestamp is None else self.timestamp)
params = [
('oauth_nonce', nonce),
('oauth_timestamp', timestamp),
('oauth_version', '1.0'),
('oauth_signature_method', self.signature_method),
('oauth_consumer_key', self.client_key),
]
if self.resource_owner_key:
params.append(('oauth_token', self.resource_owner_key))
if self.callback_uri:
params.append(('oauth_callback', self.callback_uri))
if self.verifier:
params.append(('oauth_verifier', self.verifier))
# providing body hash for requests other than x-www-form-urlencoded
# as described in https://tools.ietf.org/html/draft-eaton-oauth-bodyhash-00#section-4.1.1
# 4.1.1. When to include the body hash
# * [...] MUST NOT include an oauth_body_hash parameter on requests with form-encoded request bodies
# * [...] SHOULD include the oauth_body_hash parameter on all other requests.
# Note that SHA-1 is vulnerable. The spec acknowledges that in https://tools.ietf.org/html/draft-eaton-oauth-bodyhash-00#section-6.2
# At this time, no further effort has been made to replace SHA-1 for the OAuth Request Body Hash extension.
content_type = request.headers.get('Content-Type', None)
content_type_eligible = content_type and content_type.find('application/x-www-form-urlencoded') < 0
if request.body is not None and content_type_eligible:
params.append(('oauth_body_hash', base64.b64encode(hashlib.sha1(request.body.encode('utf-8')).digest()).decode('utf-8')))
return params | ['def', 'get_oauth_params', '(', 'self', ',', 'request', ')', ':', 'nonce', '=', '(', 'generate_nonce', '(', ')', 'if', 'self', '.', 'nonce', 'is', 'None', 'else', 'self', '.', 'nonce', ')', 'timestamp', '=', '(', 'generate_timestamp', '(', ')', 'if', 'self', '.', 'timestamp', 'is', 'None', 'else', 'self', '.', 'timestamp', ')', 'params', '=', '[', '(', "'oauth_nonce'", ',', 'nonce', ')', ',', '(', "'oauth_timestamp'", ',', 'timestamp', ')', ',', '(', "'oauth_version'", ',', "'1.0'", ')', ',', '(', "'oauth_signature_method'", ',', 'self', '.', 'signature_method', ')', ',', '(', "'oauth_consumer_key'", ',', 'self', '.', 'client_key', ')', ',', ']', 'if', 'self', '.', 'resource_owner_key', ':', 'params', '.', 'append', '(', '(', "'oauth_token'", ',', 'self', '.', 'resource_owner_key', ')', ')', 'if', 'self', '.', 'callback_uri', ':', 'params', '.', 'append', '(', '(', "'oauth_callback'", ',', 'self', '.', 'callback_uri', ')', ')', 'if', 'self', '.', 'verifier', ':', 'params', '.', 'append', '(', '(', "'oauth_verifier'", ',', 'self', '.', 'verifier', ')', ')', '# providing body hash for requests other than x-www-form-urlencoded', '# as described in https://tools.ietf.org/html/draft-eaton-oauth-bodyhash-00#section-4.1.1', '# 4.1.1. When to include the body hash', '# * [...] MUST NOT include an oauth_body_hash parameter on requests with form-encoded request bodies', '# * [...] SHOULD include the oauth_body_hash parameter on all other requests.', '# Note that SHA-1 is vulnerable. The spec acknowledges that in https://tools.ietf.org/html/draft-eaton-oauth-bodyhash-00#section-6.2', '# At this time, no further effort has been made to replace SHA-1 for the OAuth Request Body Hash extension.', 'content_type', '=', 'request', '.', 'headers', '.', 'get', '(', "'Content-Type'", ',', 'None', ')', 'content_type_eligible', '=', 'content_type', 'and', 'content_type', '.', 'find', '(', "'application/x-www-form-urlencoded'", ')', '<', '0', 'if', 'request', '.', 'body', 'is', 'not', 'None', 'and', 'content_type_eligible', ':', 'params', '.', 'append', '(', '(', "'oauth_body_hash'", ',', 'base64', '.', 'b64encode', '(', 'hashlib', '.', 'sha1', '(', 'request', '.', 'body', '.', 'encode', '(', "'utf-8'", ')', ')', '.', 'digest', '(', ')', ')', '.', 'decode', '(', "'utf-8'", ')', ')', ')', 'return', 'params'] | Get the basic OAuth parameters to be used in generating a signature. | ['Get', 'the', 'basic', 'OAuth', 'parameters', 'to', 'be', 'used', 'in', 'generating', 'a', 'signature', '.'] | train | https://github.com/oauthlib/oauthlib/blob/30321dd3c0ca784d3508a1970cf90d9f76835c79/oauthlib/oauth1/rfc5849/__init__.py#L153-L186 |
6,291 | guaix-ucm/pyemir | emirdrp/processing/bardetect.py | position_half_h | def position_half_h(pslit, cpix, backw=4):
"""Find the position where the value is half of the peak"""
# Find the first peak to the right of cpix
next_peak = simple_prot(pslit, cpix)
if next_peak is None:
raise ValueError
dis_peak = next_peak - cpix
wpos2 = cpix - dis_peak
wpos1 = wpos2 - backw
# Compute background in a window of width backw
# in a position simetrical to the peak
# around cpix
left_background = pslit[wpos1:wpos2].min()
# height of the peak
height = pslit[next_peak] - left_background
half_height = left_background + 0.5 * height
# Position at halg peak, linear interpolation
vv = pslit[wpos1:next_peak+1] - half_height
res1, = numpy.nonzero(numpy.diff(vv > 0))
i1 = res1[0]
xint = wpos1 + i1 + (0 - vv[i1]) / (vv[i1+1] - vv[i1])
return xint, next_peak, wpos1, wpos2, left_background, half_height | python | def position_half_h(pslit, cpix, backw=4):
"""Find the position where the value is half of the peak"""
# Find the first peak to the right of cpix
next_peak = simple_prot(pslit, cpix)
if next_peak is None:
raise ValueError
dis_peak = next_peak - cpix
wpos2 = cpix - dis_peak
wpos1 = wpos2 - backw
# Compute background in a window of width backw
# in a position simetrical to the peak
# around cpix
left_background = pslit[wpos1:wpos2].min()
# height of the peak
height = pslit[next_peak] - left_background
half_height = left_background + 0.5 * height
# Position at halg peak, linear interpolation
vv = pslit[wpos1:next_peak+1] - half_height
res1, = numpy.nonzero(numpy.diff(vv > 0))
i1 = res1[0]
xint = wpos1 + i1 + (0 - vv[i1]) / (vv[i1+1] - vv[i1])
return xint, next_peak, wpos1, wpos2, left_background, half_height | ['def', 'position_half_h', '(', 'pslit', ',', 'cpix', ',', 'backw', '=', '4', ')', ':', '# Find the first peak to the right of cpix', 'next_peak', '=', 'simple_prot', '(', 'pslit', ',', 'cpix', ')', 'if', 'next_peak', 'is', 'None', ':', 'raise', 'ValueError', 'dis_peak', '=', 'next_peak', '-', 'cpix', 'wpos2', '=', 'cpix', '-', 'dis_peak', 'wpos1', '=', 'wpos2', '-', 'backw', '# Compute background in a window of width backw', '# in a position simetrical to the peak', '# around cpix', 'left_background', '=', 'pslit', '[', 'wpos1', ':', 'wpos2', ']', '.', 'min', '(', ')', '# height of the peak', 'height', '=', 'pslit', '[', 'next_peak', ']', '-', 'left_background', 'half_height', '=', 'left_background', '+', '0.5', '*', 'height', '# Position at halg peak, linear interpolation', 'vv', '=', 'pslit', '[', 'wpos1', ':', 'next_peak', '+', '1', ']', '-', 'half_height', 'res1', ',', '=', 'numpy', '.', 'nonzero', '(', 'numpy', '.', 'diff', '(', 'vv', '>', '0', ')', ')', 'i1', '=', 'res1', '[', '0', ']', 'xint', '=', 'wpos1', '+', 'i1', '+', '(', '0', '-', 'vv', '[', 'i1', ']', ')', '/', '(', 'vv', '[', 'i1', '+', '1', ']', '-', 'vv', '[', 'i1', ']', ')', 'return', 'xint', ',', 'next_peak', ',', 'wpos1', ',', 'wpos2', ',', 'left_background', ',', 'half_height'] | Find the position where the value is half of the peak | ['Find', 'the', 'position', 'where', 'the', 'value', 'is', 'half', 'of', 'the', 'peak'] | train | https://github.com/guaix-ucm/pyemir/blob/fef6bbabcb13f80123cafd1800a0f508a3c21702/emirdrp/processing/bardetect.py#L123-L155 |
6,292 | melizalab/arf | arf.py | convert_timestamp | def convert_timestamp(obj):
"""Make an ARF timestamp from an object.
Argument can be a datetime.datetime object, a time.struct_time, an integer,
a float, or a tuple of integers. The returned value is a numpy array with
the integer number of seconds since the Epoch and any additional
microseconds.
Note that because floating point values are approximate, the conversion
between float and integer tuple may not be reversible.
"""
import numbers
from datetime import datetime
from time import mktime, struct_time
from numpy import zeros
out = zeros(2, dtype='int64')
if isinstance(obj, datetime):
out[0] = mktime(obj.timetuple())
out[1] = obj.microsecond
elif isinstance(obj, struct_time):
out[0] = mktime(obj)
elif isinstance(obj, numbers.Integral):
out[0] = obj
elif isinstance(obj, numbers.Real):
out[0] = obj
out[1] = (obj - out[0]) * 1e6
else:
try:
out[:2] = obj[:2]
except:
raise TypeError("unable to convert %s to timestamp" % obj)
return out | python | def convert_timestamp(obj):
"""Make an ARF timestamp from an object.
Argument can be a datetime.datetime object, a time.struct_time, an integer,
a float, or a tuple of integers. The returned value is a numpy array with
the integer number of seconds since the Epoch and any additional
microseconds.
Note that because floating point values are approximate, the conversion
between float and integer tuple may not be reversible.
"""
import numbers
from datetime import datetime
from time import mktime, struct_time
from numpy import zeros
out = zeros(2, dtype='int64')
if isinstance(obj, datetime):
out[0] = mktime(obj.timetuple())
out[1] = obj.microsecond
elif isinstance(obj, struct_time):
out[0] = mktime(obj)
elif isinstance(obj, numbers.Integral):
out[0] = obj
elif isinstance(obj, numbers.Real):
out[0] = obj
out[1] = (obj - out[0]) * 1e6
else:
try:
out[:2] = obj[:2]
except:
raise TypeError("unable to convert %s to timestamp" % obj)
return out | ['def', 'convert_timestamp', '(', 'obj', ')', ':', 'import', 'numbers', 'from', 'datetime', 'import', 'datetime', 'from', 'time', 'import', 'mktime', ',', 'struct_time', 'from', 'numpy', 'import', 'zeros', 'out', '=', 'zeros', '(', '2', ',', 'dtype', '=', "'int64'", ')', 'if', 'isinstance', '(', 'obj', ',', 'datetime', ')', ':', 'out', '[', '0', ']', '=', 'mktime', '(', 'obj', '.', 'timetuple', '(', ')', ')', 'out', '[', '1', ']', '=', 'obj', '.', 'microsecond', 'elif', 'isinstance', '(', 'obj', ',', 'struct_time', ')', ':', 'out', '[', '0', ']', '=', 'mktime', '(', 'obj', ')', 'elif', 'isinstance', '(', 'obj', ',', 'numbers', '.', 'Integral', ')', ':', 'out', '[', '0', ']', '=', 'obj', 'elif', 'isinstance', '(', 'obj', ',', 'numbers', '.', 'Real', ')', ':', 'out', '[', '0', ']', '=', 'obj', 'out', '[', '1', ']', '=', '(', 'obj', '-', 'out', '[', '0', ']', ')', '*', '1e6', 'else', ':', 'try', ':', 'out', '[', ':', '2', ']', '=', 'obj', '[', ':', '2', ']', 'except', ':', 'raise', 'TypeError', '(', '"unable to convert %s to timestamp"', '%', 'obj', ')', 'return', 'out'] | Make an ARF timestamp from an object.
Argument can be a datetime.datetime object, a time.struct_time, an integer,
a float, or a tuple of integers. The returned value is a numpy array with
the integer number of seconds since the Epoch and any additional
microseconds.
Note that because floating point values are approximate, the conversion
between float and integer tuple may not be reversible. | ['Make', 'an', 'ARF', 'timestamp', 'from', 'an', 'object', '.'] | train | https://github.com/melizalab/arf/blob/71746d9edbe7993a783d4acaf84b9631f3230283/arf.py#L280-L313 |
6,293 | O365/python-o365 | O365/utils/token.py | BaseTokenBackend.token | def token(self, value):
""" Setter to convert any token dict into Token instance """
if value and not isinstance(value, Token):
value = Token(value)
self._token = value | python | def token(self, value):
""" Setter to convert any token dict into Token instance """
if value and not isinstance(value, Token):
value = Token(value)
self._token = value | ['def', 'token', '(', 'self', ',', 'value', ')', ':', 'if', 'value', 'and', 'not', 'isinstance', '(', 'value', ',', 'Token', ')', ':', 'value', '=', 'Token', '(', 'value', ')', 'self', '.', '_token', '=', 'value'] | Setter to convert any token dict into Token instance | ['Setter', 'to', 'convert', 'any', 'token', 'dict', 'into', 'Token', 'instance'] | train | https://github.com/O365/python-o365/blob/02a71cf3775cc6a3c042e003365d6a07c8c75a73/O365/utils/token.py#L63-L67 |
6,294 | ladybug-tools/ladybug | ladybug/psychrometrics.py | db_temp_from_wb_rh | def db_temp_from_wb_rh(wet_bulb, rel_humid, b_press=101325):
"""Dry Bulb Temperature (C) and humidity_ratio at at wet_bulb (C),
rel_humid (%) and Pressure b_press (Pa).
Formula is only valid for rel_humid == 0 or rel_humid == 100.
"""
assert rel_humid == 0 or rel_humid == 100, 'formula is only valid for' \
' rel_humid == 0 or rel_humid == 100'
humidity_ratio = humid_ratio_from_db_rh(wet_bulb, rel_humid, b_press)
hr_saturation = humid_ratio_from_db_rh(wet_bulb, 100, b_press)
db_temp = wet_bulb + (((hr_saturation - humidity_ratio) * 2260000) / (1005))
return db_temp, humidity_ratio | python | def db_temp_from_wb_rh(wet_bulb, rel_humid, b_press=101325):
"""Dry Bulb Temperature (C) and humidity_ratio at at wet_bulb (C),
rel_humid (%) and Pressure b_press (Pa).
Formula is only valid for rel_humid == 0 or rel_humid == 100.
"""
assert rel_humid == 0 or rel_humid == 100, 'formula is only valid for' \
' rel_humid == 0 or rel_humid == 100'
humidity_ratio = humid_ratio_from_db_rh(wet_bulb, rel_humid, b_press)
hr_saturation = humid_ratio_from_db_rh(wet_bulb, 100, b_press)
db_temp = wet_bulb + (((hr_saturation - humidity_ratio) * 2260000) / (1005))
return db_temp, humidity_ratio | ['def', 'db_temp_from_wb_rh', '(', 'wet_bulb', ',', 'rel_humid', ',', 'b_press', '=', '101325', ')', ':', 'assert', 'rel_humid', '==', '0', 'or', 'rel_humid', '==', '100', ',', "'formula is only valid for'", "' rel_humid == 0 or rel_humid == 100'", 'humidity_ratio', '=', 'humid_ratio_from_db_rh', '(', 'wet_bulb', ',', 'rel_humid', ',', 'b_press', ')', 'hr_saturation', '=', 'humid_ratio_from_db_rh', '(', 'wet_bulb', ',', '100', ',', 'b_press', ')', 'db_temp', '=', 'wet_bulb', '+', '(', '(', '(', 'hr_saturation', '-', 'humidity_ratio', ')', '*', '2260000', ')', '/', '(', '1005', ')', ')', 'return', 'db_temp', ',', 'humidity_ratio'] | Dry Bulb Temperature (C) and humidity_ratio at at wet_bulb (C),
rel_humid (%) and Pressure b_press (Pa).
Formula is only valid for rel_humid == 0 or rel_humid == 100. | ['Dry', 'Bulb', 'Temperature', '(', 'C', ')', 'and', 'humidity_ratio', 'at', 'at', 'wet_bulb', '(', 'C', ')', 'rel_humid', '(', '%', ')', 'and', 'Pressure', 'b_press', '(', 'Pa', ')', '.'] | train | https://github.com/ladybug-tools/ladybug/blob/c08b7308077a48d5612f644943f92d5b5dade583/ladybug/psychrometrics.py#L212-L223 |
6,295 | thumbor/thumbor | thumbor/metrics/statsd_metrics.py | Metrics.client | def client(cls, config):
"""
Cache statsd client so it doesn't do a DNS lookup
over and over
"""
if not hasattr(cls, "_client"):
cls._client = statsd.StatsClient(config.STATSD_HOST, config.STATSD_PORT, config.STATSD_PREFIX)
return cls._client | python | def client(cls, config):
"""
Cache statsd client so it doesn't do a DNS lookup
over and over
"""
if not hasattr(cls, "_client"):
cls._client = statsd.StatsClient(config.STATSD_HOST, config.STATSD_PORT, config.STATSD_PREFIX)
return cls._client | ['def', 'client', '(', 'cls', ',', 'config', ')', ':', 'if', 'not', 'hasattr', '(', 'cls', ',', '"_client"', ')', ':', 'cls', '.', '_client', '=', 'statsd', '.', 'StatsClient', '(', 'config', '.', 'STATSD_HOST', ',', 'config', '.', 'STATSD_PORT', ',', 'config', '.', 'STATSD_PREFIX', ')', 'return', 'cls', '.', '_client'] | Cache statsd client so it doesn't do a DNS lookup
over and over | ['Cache', 'statsd', 'client', 'so', 'it', 'doesn', 't', 'do', 'a', 'DNS', 'lookup', 'over', 'and', 'over'] | train | https://github.com/thumbor/thumbor/blob/558ccdd6e3bc29e1c9ee3687372c4b3eb05ac607/thumbor/metrics/statsd_metrics.py#L18-L25 |
6,296 | biolink/ontobio | ontobio/sim/api/owlsim2.py | OwlSim2Api._simsearch_to_simresult | def _simsearch_to_simresult(self, sim_resp: Dict, method: SimAlgorithm) -> SimResult:
"""
Convert owlsim json to SimResult object
:param sim_resp: owlsim response from search_by_attribute_set()
:param method: SimAlgorithm
:return: SimResult object
"""
sim_ids = get_nodes_from_ids(sim_resp['query_IRIs'])
sim_resp['results'] = OwlSim2Api._rank_results(sim_resp['results'], method)
# get id type map:
ids = [result['j']['id'] for result in sim_resp['results']]
id_type_map = get_id_type_map(ids)
matches = []
for result in sim_resp['results']:
matches.append(
SimMatch(
id=result['j']['id'],
label=result['j']['label'],
rank=result['rank'],
score=result[OwlSim2Api.method2key[method]],
type=id_type_map[result['j']['id']][0],
taxon=get_taxon(result['j']['id']),
significance="NaN",
pairwise_match=OwlSim2Api._make_pairwise_matches(result)
)
)
return SimResult(
query=SimQuery(
ids=sim_ids,
unresolved_ids=sim_resp['unresolved'],
target_ids=[[]]
),
matches=matches,
metadata=SimMetadata(
max_max_ic=self.statistics.max_max_ic
)
) | python | def _simsearch_to_simresult(self, sim_resp: Dict, method: SimAlgorithm) -> SimResult:
"""
Convert owlsim json to SimResult object
:param sim_resp: owlsim response from search_by_attribute_set()
:param method: SimAlgorithm
:return: SimResult object
"""
sim_ids = get_nodes_from_ids(sim_resp['query_IRIs'])
sim_resp['results'] = OwlSim2Api._rank_results(sim_resp['results'], method)
# get id type map:
ids = [result['j']['id'] for result in sim_resp['results']]
id_type_map = get_id_type_map(ids)
matches = []
for result in sim_resp['results']:
matches.append(
SimMatch(
id=result['j']['id'],
label=result['j']['label'],
rank=result['rank'],
score=result[OwlSim2Api.method2key[method]],
type=id_type_map[result['j']['id']][0],
taxon=get_taxon(result['j']['id']),
significance="NaN",
pairwise_match=OwlSim2Api._make_pairwise_matches(result)
)
)
return SimResult(
query=SimQuery(
ids=sim_ids,
unresolved_ids=sim_resp['unresolved'],
target_ids=[[]]
),
matches=matches,
metadata=SimMetadata(
max_max_ic=self.statistics.max_max_ic
)
) | ['def', '_simsearch_to_simresult', '(', 'self', ',', 'sim_resp', ':', 'Dict', ',', 'method', ':', 'SimAlgorithm', ')', '->', 'SimResult', ':', 'sim_ids', '=', 'get_nodes_from_ids', '(', 'sim_resp', '[', "'query_IRIs'", ']', ')', 'sim_resp', '[', "'results'", ']', '=', 'OwlSim2Api', '.', '_rank_results', '(', 'sim_resp', '[', "'results'", ']', ',', 'method', ')', '# get id type map:', 'ids', '=', '[', 'result', '[', "'j'", ']', '[', "'id'", ']', 'for', 'result', 'in', 'sim_resp', '[', "'results'", ']', ']', 'id_type_map', '=', 'get_id_type_map', '(', 'ids', ')', 'matches', '=', '[', ']', 'for', 'result', 'in', 'sim_resp', '[', "'results'", ']', ':', 'matches', '.', 'append', '(', 'SimMatch', '(', 'id', '=', 'result', '[', "'j'", ']', '[', "'id'", ']', ',', 'label', '=', 'result', '[', "'j'", ']', '[', "'label'", ']', ',', 'rank', '=', 'result', '[', "'rank'", ']', ',', 'score', '=', 'result', '[', 'OwlSim2Api', '.', 'method2key', '[', 'method', ']', ']', ',', 'type', '=', 'id_type_map', '[', 'result', '[', "'j'", ']', '[', "'id'", ']', ']', '[', '0', ']', ',', 'taxon', '=', 'get_taxon', '(', 'result', '[', "'j'", ']', '[', "'id'", ']', ')', ',', 'significance', '=', '"NaN"', ',', 'pairwise_match', '=', 'OwlSim2Api', '.', '_make_pairwise_matches', '(', 'result', ')', ')', ')', 'return', 'SimResult', '(', 'query', '=', 'SimQuery', '(', 'ids', '=', 'sim_ids', ',', 'unresolved_ids', '=', 'sim_resp', '[', "'unresolved'", ']', ',', 'target_ids', '=', '[', '[', ']', ']', ')', ',', 'matches', '=', 'matches', ',', 'metadata', '=', 'SimMetadata', '(', 'max_max_ic', '=', 'self', '.', 'statistics', '.', 'max_max_ic', ')', ')'] | Convert owlsim json to SimResult object
:param sim_resp: owlsim response from search_by_attribute_set()
:param method: SimAlgorithm
:return: SimResult object | ['Convert', 'owlsim', 'json', 'to', 'SimResult', 'object'] | train | https://github.com/biolink/ontobio/blob/4e512a7831cfe6bc1b32f2c3be2ba41bc5cf7345/ontobio/sim/api/owlsim2.py#L311-L353 |
6,297 | Azure/azure-cli-extensions | src/alias/azext_alias/alias.py | AliasManager.load_collided_alias | def load_collided_alias(self):
"""
Load (create, if not exist) the collided alias file.
"""
# w+ creates the alias config file if it does not exist
open_mode = 'r+' if os.path.exists(GLOBAL_COLLIDED_ALIAS_PATH) else 'w+'
with open(GLOBAL_COLLIDED_ALIAS_PATH, open_mode) as collided_alias_file:
collided_alias_str = collided_alias_file.read()
try:
self.collided_alias = json.loads(collided_alias_str if collided_alias_str else '{}')
except Exception: # pylint: disable=broad-except
self.collided_alias = {} | python | def load_collided_alias(self):
"""
Load (create, if not exist) the collided alias file.
"""
# w+ creates the alias config file if it does not exist
open_mode = 'r+' if os.path.exists(GLOBAL_COLLIDED_ALIAS_PATH) else 'w+'
with open(GLOBAL_COLLIDED_ALIAS_PATH, open_mode) as collided_alias_file:
collided_alias_str = collided_alias_file.read()
try:
self.collided_alias = json.loads(collided_alias_str if collided_alias_str else '{}')
except Exception: # pylint: disable=broad-except
self.collided_alias = {} | ['def', 'load_collided_alias', '(', 'self', ')', ':', '# w+ creates the alias config file if it does not exist', 'open_mode', '=', "'r+'", 'if', 'os', '.', 'path', '.', 'exists', '(', 'GLOBAL_COLLIDED_ALIAS_PATH', ')', 'else', "'w+'", 'with', 'open', '(', 'GLOBAL_COLLIDED_ALIAS_PATH', ',', 'open_mode', ')', 'as', 'collided_alias_file', ':', 'collided_alias_str', '=', 'collided_alias_file', '.', 'read', '(', ')', 'try', ':', 'self', '.', 'collided_alias', '=', 'json', '.', 'loads', '(', 'collided_alias_str', 'if', 'collided_alias_str', 'else', "'{}'", ')', 'except', 'Exception', ':', '# pylint: disable=broad-except', 'self', '.', 'collided_alias', '=', '{', '}'] | Load (create, if not exist) the collided alias file. | ['Load', '(', 'create', 'if', 'not', 'exist', ')', 'the', 'collided', 'alias', 'file', '.'] | train | https://github.com/Azure/azure-cli-extensions/blob/3d4854205b0f0d882f688cfa12383d14506c2e35/src/alias/azext_alias/alias.py#L79-L90 |
6,298 | hosford42/xcs | xcs/algorithms/xcs.py | XCSAlgorithm._action_set_subsumption | def _action_set_subsumption(self, action_set):
"""Perform action set subsumption."""
# Select a condition with maximum bit count among those having
# sufficient experience and sufficiently low error.
selected_rule = None
selected_bit_count = None
for rule in action_set:
if not (rule.experience > self.subsumption_threshold and
rule.error < self.error_threshold):
continue
bit_count = rule.condition.count()
if (selected_rule is None or
bit_count > selected_bit_count or
(bit_count == selected_bit_count and
random.randrange(2))):
selected_rule = rule
selected_bit_count = bit_count
# If no rule was found satisfying the requirements, return
# early.
if selected_rule is None:
return
# Subsume each rule which the selected rule generalizes. When a
# rule is subsumed, all instances of the subsumed rule are replaced
# with instances of the more general one in the population.
to_remove = []
for rule in action_set:
if (selected_rule is not rule and
selected_rule.condition(rule.condition)):
selected_rule.numerosity += rule.numerosity
action_set.model.discard(rule, rule.numerosity)
to_remove.append(rule)
for rule in to_remove:
action_set.remove(rule) | python | def _action_set_subsumption(self, action_set):
"""Perform action set subsumption."""
# Select a condition with maximum bit count among those having
# sufficient experience and sufficiently low error.
selected_rule = None
selected_bit_count = None
for rule in action_set:
if not (rule.experience > self.subsumption_threshold and
rule.error < self.error_threshold):
continue
bit_count = rule.condition.count()
if (selected_rule is None or
bit_count > selected_bit_count or
(bit_count == selected_bit_count and
random.randrange(2))):
selected_rule = rule
selected_bit_count = bit_count
# If no rule was found satisfying the requirements, return
# early.
if selected_rule is None:
return
# Subsume each rule which the selected rule generalizes. When a
# rule is subsumed, all instances of the subsumed rule are replaced
# with instances of the more general one in the population.
to_remove = []
for rule in action_set:
if (selected_rule is not rule and
selected_rule.condition(rule.condition)):
selected_rule.numerosity += rule.numerosity
action_set.model.discard(rule, rule.numerosity)
to_remove.append(rule)
for rule in to_remove:
action_set.remove(rule) | ['def', '_action_set_subsumption', '(', 'self', ',', 'action_set', ')', ':', '# Select a condition with maximum bit count among those having', '# sufficient experience and sufficiently low error.', 'selected_rule', '=', 'None', 'selected_bit_count', '=', 'None', 'for', 'rule', 'in', 'action_set', ':', 'if', 'not', '(', 'rule', '.', 'experience', '>', 'self', '.', 'subsumption_threshold', 'and', 'rule', '.', 'error', '<', 'self', '.', 'error_threshold', ')', ':', 'continue', 'bit_count', '=', 'rule', '.', 'condition', '.', 'count', '(', ')', 'if', '(', 'selected_rule', 'is', 'None', 'or', 'bit_count', '>', 'selected_bit_count', 'or', '(', 'bit_count', '==', 'selected_bit_count', 'and', 'random', '.', 'randrange', '(', '2', ')', ')', ')', ':', 'selected_rule', '=', 'rule', 'selected_bit_count', '=', 'bit_count', '# If no rule was found satisfying the requirements, return', '# early.', 'if', 'selected_rule', 'is', 'None', ':', 'return', '# Subsume each rule which the selected rule generalizes. When a', '# rule is subsumed, all instances of the subsumed rule are replaced', '# with instances of the more general one in the population.', 'to_remove', '=', '[', ']', 'for', 'rule', 'in', 'action_set', ':', 'if', '(', 'selected_rule', 'is', 'not', 'rule', 'and', 'selected_rule', '.', 'condition', '(', 'rule', '.', 'condition', ')', ')', ':', 'selected_rule', '.', 'numerosity', '+=', 'rule', '.', 'numerosity', 'action_set', '.', 'model', '.', 'discard', '(', 'rule', ',', 'rule', '.', 'numerosity', ')', 'to_remove', '.', 'append', '(', 'rule', ')', 'for', 'rule', 'in', 'to_remove', ':', 'action_set', '.', 'remove', '(', 'rule', ')'] | Perform action set subsumption. | ['Perform', 'action', 'set', 'subsumption', '.'] | train | https://github.com/hosford42/xcs/blob/183bdd0dd339e19ded3be202f86e1b38bdb9f1e5/xcs/algorithms/xcs.py#L779-L813 |
6,299 | marcomusy/vtkplotter | vtkplotter/actors.py | Actor.subdivide | def subdivide(self, N=1, method=0):
"""Increase the number of vertices of a surface mesh.
:param int N: number of subdivisions.
:param int method: Loop(0), Linear(1), Adaptive(2), Butterfly(3)
.. hint:: |tutorial_subdivide| |tutorial.py|_
"""
triangles = vtk.vtkTriangleFilter()
triangles.SetInputData(self.polydata())
triangles.Update()
originalMesh = triangles.GetOutput()
if method == 0:
sdf = vtk.vtkLoopSubdivisionFilter()
elif method == 1:
sdf = vtk.vtkLinearSubdivisionFilter()
elif method == 2:
sdf = vtk.vtkAdaptiveSubdivisionFilter()
elif method == 3:
sdf = vtk.vtkButterflySubdivisionFilter()
else:
colors.printc("~times Error in subdivide: unknown method.", c="r")
exit()
if method != 2:
sdf.SetNumberOfSubdivisions(N)
sdf.SetInputData(originalMesh)
sdf.Update()
return self.updateMesh(sdf.GetOutput()) | python | def subdivide(self, N=1, method=0):
"""Increase the number of vertices of a surface mesh.
:param int N: number of subdivisions.
:param int method: Loop(0), Linear(1), Adaptive(2), Butterfly(3)
.. hint:: |tutorial_subdivide| |tutorial.py|_
"""
triangles = vtk.vtkTriangleFilter()
triangles.SetInputData(self.polydata())
triangles.Update()
originalMesh = triangles.GetOutput()
if method == 0:
sdf = vtk.vtkLoopSubdivisionFilter()
elif method == 1:
sdf = vtk.vtkLinearSubdivisionFilter()
elif method == 2:
sdf = vtk.vtkAdaptiveSubdivisionFilter()
elif method == 3:
sdf = vtk.vtkButterflySubdivisionFilter()
else:
colors.printc("~times Error in subdivide: unknown method.", c="r")
exit()
if method != 2:
sdf.SetNumberOfSubdivisions(N)
sdf.SetInputData(originalMesh)
sdf.Update()
return self.updateMesh(sdf.GetOutput()) | ['def', 'subdivide', '(', 'self', ',', 'N', '=', '1', ',', 'method', '=', '0', ')', ':', 'triangles', '=', 'vtk', '.', 'vtkTriangleFilter', '(', ')', 'triangles', '.', 'SetInputData', '(', 'self', '.', 'polydata', '(', ')', ')', 'triangles', '.', 'Update', '(', ')', 'originalMesh', '=', 'triangles', '.', 'GetOutput', '(', ')', 'if', 'method', '==', '0', ':', 'sdf', '=', 'vtk', '.', 'vtkLoopSubdivisionFilter', '(', ')', 'elif', 'method', '==', '1', ':', 'sdf', '=', 'vtk', '.', 'vtkLinearSubdivisionFilter', '(', ')', 'elif', 'method', '==', '2', ':', 'sdf', '=', 'vtk', '.', 'vtkAdaptiveSubdivisionFilter', '(', ')', 'elif', 'method', '==', '3', ':', 'sdf', '=', 'vtk', '.', 'vtkButterflySubdivisionFilter', '(', ')', 'else', ':', 'colors', '.', 'printc', '(', '"~times Error in subdivide: unknown method."', ',', 'c', '=', '"r"', ')', 'exit', '(', ')', 'if', 'method', '!=', '2', ':', 'sdf', '.', 'SetNumberOfSubdivisions', '(', 'N', ')', 'sdf', '.', 'SetInputData', '(', 'originalMesh', ')', 'sdf', '.', 'Update', '(', ')', 'return', 'self', '.', 'updateMesh', '(', 'sdf', '.', 'GetOutput', '(', ')', ')'] | Increase the number of vertices of a surface mesh.
:param int N: number of subdivisions.
:param int method: Loop(0), Linear(1), Adaptive(2), Butterfly(3)
.. hint:: |tutorial_subdivide| |tutorial.py|_ | ['Increase', 'the', 'number', 'of', 'vertices', 'of', 'a', 'surface', 'mesh', '.'] | train | https://github.com/marcomusy/vtkplotter/blob/692c3396782722ec525bc1346a26999868c650c6/vtkplotter/actors.py#L1858-L1885 |
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