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xeroc/python-graphenelib | graphenebase/account.py | https://github.com/xeroc/python-graphenelib/blob/8bb5396bc79998ee424cf3813af478304173f3a6/graphenebase/account.py#L287-L292 | def point(self):
""" Return the point for the public key """
string = unhexlify(self.unCompressed())
return ecdsa.VerifyingKey.from_string(
string[1:], curve=ecdsa.SECP256k1
).pubkey.point | [
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ray-project/ray | python/ray/utils.py | https://github.com/ray-project/ray/blob/4eade036a0505e244c976f36aaa2d64386b5129b/python/ray/utils.py#L420-L442 | def check_oversized_pickle(pickled, name, obj_type, worker):
"""Send a warning message if the pickled object is too large.
Args:
pickled: the pickled object.
name: name of the pickled object.
obj_type: type of the pickled object, can be 'function',
'remote function', 'actor', or 'object'.
worker: the worker used to send warning message.
"""
length = len(pickled)
if length <= ray_constants.PICKLE_OBJECT_WARNING_SIZE:
return
warning_message = (
"Warning: The {} {} has size {} when pickled. "
"It will be stored in Redis, which could cause memory issues. "
"This may mean that its definition uses a large array or other object."
).format(obj_type, name, length)
push_error_to_driver(
worker,
ray_constants.PICKLING_LARGE_OBJECT_PUSH_ERROR,
warning_message,
driver_id=worker.task_driver_id) | [
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cosven/feeluown-core | fuocore/utils.py | https://github.com/cosven/feeluown-core/blob/62dc64638f62971b16be0a75c0b8c7ae2999869e/fuocore/utils.py#L43-L69 | def find_previous(element, l):
"""
find previous element in a sorted list
>>> find_previous(0, [0])
0
>>> find_previous(2, [1, 1, 3])
1
>>> find_previous(0, [1, 2])
>>> find_previous(1.5, [1, 2])
1
>>> find_previous(3, [1, 2])
2
"""
length = len(l)
for index, current in enumerate(l):
# current is the last element
if length - 1 == index:
return current
# current is the first element
if index == 0:
if element < current:
return None
if current <= element < l[index+1]:
return current | [
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>>> find_previous(1.5, [1, 2])
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>>> find_previous(3, [1, 2])
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trailofbits/manticore | manticore/native/cpu/x86.py | https://github.com/trailofbits/manticore/blob/54c5a15b1119c523ae54c09972413e8b97f11629/manticore/native/cpu/x86.py#L5256-L5279 | def PSRLDQ(cpu, dest, src):
"""
Packed shift right logical double quadword.
Shifts the destination operand (first operand) to the right by the number
of bytes specified in the count operand (second operand). The empty high-order
bytes are cleared (set to all 0s). If the value specified by the count
operand is greater than 15, the destination operand is set to all 0s.
The destination operand is an XMM register. The count operand is an 8-bit
immediate::
TEMP = SRC;
if (TEMP > 15) TEMP = 16;
DEST = DEST >> (temp * 8);
:param cpu: current CPU.
:param dest: destination operand.
:param src: count operand.
"""
# TODO(yan): Verify the correctness of truncating SRC like this ( tests
# use '-1' as the value
temp = Operators.EXTRACT(src.read(), 0, 8)
temp = Operators.ITEBV(src.size, temp > 15, 16, temp)
dest.write(dest.read() >> (temp * 8)) | [
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KelSolaar/Umbra | umbra/components/factory/components_manager_ui/nodes.py | https://github.com/KelSolaar/Umbra/blob/66f45f08d9d723787f1191989f8b0dda84b412ce/umbra/components/factory/components_manager_ui/nodes.py#L231-L253 | def __initialize_node(self, attributes_flags=int(Qt.ItemIsSelectable | Qt.ItemIsEnabled)):
"""
Initializes the node.
:param attributes_flags: Attributes flags.
:type attributes_flags: int
"""
attributes = dir(self.__component)
for attribute in attributes:
if attribute == "name":
continue
if not "_Profile__{0}".format(attribute) in attributes:
continue
value = getattr(self.__component, attribute)
value = ", ".join(value) if type(value) in (tuple, list) else value
roles = {Qt.DisplayRole: value,
Qt.EditRole: value}
self[attribute] = umbra.ui.nodes.GraphModelAttribute(attribute, value, roles, attributes_flags)
self.update_tool_tip() | [
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NuGrid/NuGridPy | nugridpy/nugridse.py | https://github.com/NuGrid/NuGridPy/blob/eee8047446e398be77362d82c1d8b3310054fab0/nugridpy/nugridse.py#L423-L462 | def get_elemental_abunds(self,cycle,index=None):
"""
returns the elemental abundances for one cycle, either
for the whole star or a specific zone depending upon
the value of 'index'.
Parameters
----------
cycle : string or integer
Model to get the abundances for.
index : integer or list, optional
zone number for which to get elemental abundances. If
None the entire abundance profile is returned. If a 1x2
list, the abundances are returned between indices of
index[0] and index[1].
The default is None.
"""
isoabunds=self.se.get(cycle,'iso_massf')
A=array(self.se.A)
Z=array(self.se.Z)
names=self.se.isos
Zuq=list(set(Z)) # list of unique Zs
Zuq.sort()
if index==None:
index=[0,len(isoabunds)]
if type(index)==list:
elemabunds=[]
for zone in range(index[0],index[1]):
percent=int((zone-index[0])*100./(index[1]-index[0]))
sys.stdout.flush()
sys.stdout.write("\rgetting elemental abundances " + "...%d%%" % percent)
elemabunds.append([sum(isoabunds[zone][where(Z==iZ)]) for iZ in Zuq])
else:
elemabunds=[sum(isoabunds[index][where(Z==iZ)]) for iZ in Zuq]
return elemabunds | [
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index : integer or list, optional
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ajenhl/tacl | tacl/data_store.py | https://github.com/ajenhl/tacl/blob/b8a343248e77f1c07a5a4ac133a9ad6e0b4781c2/tacl/data_store.py#L162-L183 | def _add_text_size_ngrams(self, text_id, size, ngrams):
"""Adds `ngrams`, that are of size `size`, to the data store.
The added `ngrams` are associated with `text_id`.
:param text_id: database ID of text associated with `ngrams`
:type text_id: `int`
:param size: size of n-grams
:type size: `int`
:param ngrams: n-grams to be added
:type ngrams: `collections.Counter`
"""
unique_ngrams = len(ngrams)
self._logger.info('Adding {} unique {}-grams'.format(
unique_ngrams, size))
parameters = [[text_id, ngram, size, count]
for ngram, count in ngrams.items()]
with self._conn:
self._conn.execute(constants.INSERT_TEXT_HAS_NGRAM_SQL,
[text_id, size, unique_ngrams])
self._conn.executemany(constants.INSERT_NGRAM_SQL, parameters) | [
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bids-standard/pybids | bids/reports/report.py | https://github.com/bids-standard/pybids/blob/30d924ce770622bda0e390d613a8da42a2a20c32/bids/reports/report.py#L94-L147 | def _report_subject(self, subject, **kwargs):
"""Write a report for a single subject.
Parameters
----------
subject : :obj:`str`
Subject ID.
Attributes
----------
layout : :obj:`bids.layout.BIDSLayout`
Layout object for a BIDS dataset.
config : :obj:`dict`
Configuration info for methods generation.
Returns
-------
description : :obj:`str`
A publication-ready report of the dataset's data acquisition
information. Each scan type is given its own paragraph.
"""
description_list = []
# Remove sess from kwargs if provided, else set sess as all available
sessions = kwargs.pop('session',
self.layout.get_sessions(subject=subject,
**kwargs))
if not sessions:
sessions = [None]
elif not isinstance(sessions, list):
sessions = [sessions]
for ses in sessions:
niftis = self.layout.get(subject=subject, extensions='nii.gz',
**kwargs)
if niftis:
description_list.append('For session {0}:'.format(ses))
description_list += parsing.parse_niftis(self.layout, niftis,
subject, self.config,
session=ses)
metadata = self.layout.get_metadata(niftis[0].path)
else:
raise Exception('No niftis for subject {0}'.format(subject))
# Assume all data were converted the same way and use the last nifti
# file's json for conversion information.
if 'metadata' not in vars():
raise Exception('No valid jsons found. Cannot generate final '
'paragraph.')
description = '\n\t'.join(description_list)
description = description.replace('\tFor session', '\nFor session')
description += '\n\n{0}'.format(parsing.final_paragraph(metadata))
return description | [
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Layout object for a BIDS dataset.
config : :obj:`dict`
Configuration info for methods generation.
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Qiskit/qiskit-terra | qiskit/validation/base.py | https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/validation/base.py#L227-L233 | def _validate(instance):
"""Validate the internal representation of the instance."""
try:
_ = instance.schema.validate(instance.to_dict())
except ValidationError as ex:
raise ModelValidationError(
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ljcooke/see | see/output.py | https://github.com/ljcooke/see/blob/4cbc67a31c92367977ecb4bbb1f0736fa688a6ba/see/output.py#L117-L131 | def column_width(tokens):
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google/openhtf | openhtf/util/conf.py | https://github.com/google/openhtf/blob/655e85df7134db7bdf8f8fdd6ff9a6bf932e7b09/openhtf/util/conf.py#L356-L366 | def reset(self):
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decryptus/sonicprobe | sonicprobe/libs/pworkerpool.py | https://github.com/decryptus/sonicprobe/blob/72f73f3a40d2982d79ad68686e36aa31d94b76f8/sonicprobe/libs/pworkerpool.py#L188-L200 | def add(self, nb = 1, name = None):
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noobermin/pys | pys/__init__.py | https://github.com/noobermin/pys/blob/e01b74210c65eb96d019bb42e0a3c9e6676da943/pys/__init__.py#L130-L138 | def parse_ctuple(s,length=2):
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google/dotty | efilter/scope.py | https://github.com/google/dotty/blob/b145131499be0c4b755fc2e2ac19be11a50bce6a/efilter/scope.py#L104-L119 | def getmembers_runtime(self):
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asweigart/pysimplevalidate | src/pysimplevalidate/__init__.py | https://github.com/asweigart/pysimplevalidate/blob/3ca27228abb7355d14bbf8abc225c63366379e44/src/pysimplevalidate/__init__.py#L1122-L1180 | def validateYesNo(value, blank=False, strip=None, allowlistRegexes=None, blocklistRegexes=None, yesVal='yes', noVal='no', caseSensitive=False, excMsg=None):
"""Raises ValidationException if value is not a yes or no response.
Returns the yesVal or noVal argument, not value.
Note that value can be any case (by default) and can also just match the
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* caseSensitive (bool): Determines if value must match the case of yesVal and noVal. Defaults to False.
* excMsg (str): A custom message to use in the raised ValidationException.
>>> import pysimplevalidate as pysv
>>> pysv.validateYesNo('y')
'yes'
>>> pysv.validateYesNo('YES')
'yes'
>>> pysv.validateYesNo('No')
'no'
>>> pysv.validateYesNo('OUI', yesVal='oui', noVal='no')
'oui'
"""
# Validate parameters. TODO - can probably improve this to remove the duplication.
_validateGenericParameters(blank=blank, strip=strip, allowlistRegexes=allowlistRegexes, blocklistRegexes=blocklistRegexes)
returnNow, value = _prevalidationCheck(value, blank, strip, allowlistRegexes, blocklistRegexes, excMsg)
if returnNow:
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yesVal = str(yesVal)
noVal = str(noVal)
if len(yesVal) == 0:
raise PySimpleValidateException('yesVal argument must be a non-empty string.')
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raise PySimpleValidateException('noVal argument must be a non-empty string.')
if (yesVal == noVal) or (not caseSensitive and yesVal.upper() == noVal.upper()):
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if (yesVal[0] == noVal[0]) or (not caseSensitive and yesVal[0].upper() == noVal[0].upper()):
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returnNow, value = _prevalidationCheck(value, blank, strip, allowlistRegexes, blocklistRegexes, excMsg)
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hydpy-dev/hydpy | hydpy/auxs/anntools.py | https://github.com/hydpy-dev/hydpy/blob/1bc6a82cf30786521d86b36e27900c6717d3348d/hydpy/auxs/anntools.py#L1471-L1473 | def shape(self) -> Tuple[int, ...]:
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inveniosoftware/invenio-records-rest | invenio_records_rest/serializers/jsonld.py | https://github.com/inveniosoftware/invenio-records-rest/blob/e7b63c5f72cef03d06d3f1b4c12c0d37e3a628b9/invenio_records_rest/serializers/jsonld.py#L70-L76 | def transform_search_hit(self, pid, record_hit, links_factory=None,
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ArchiveTeam/wpull | wpull/protocol/http/robots.py | https://github.com/ArchiveTeam/wpull/blob/ddf051aa3322479325ba20aa778cb2cb97606bf5/wpull/protocol/http/robots.py#L61-L96 | def fetch_robots_txt(self, request: Request, file=None):
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Coroutine.
'''
url_info = request.url_info
url = URLInfo.parse('{0}://{1}/robots.txt'.format(
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self._accept_as_blank(url_info)
return
status_code = response.status_code
if 500 <= status_code <= 599:
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if status_code == 200:
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RomelTorres/alpha_vantage | alpha_vantage/alphavantage.py | https://github.com/RomelTorres/alpha_vantage/blob/4e0b5057e520e3e3de69cf947301765817290121/alpha_vantage/alphavantage.py#L214-L241 | def map_to_matype(self, matype):
""" Convert to the alpha vantage math type integer. It returns an
integer correspondent to the type of math to apply to a function. It
raises ValueError if an integer greater than the supported math types
is given.
Keyword Arguments:
matype: The math type of the alpha vantage api. It accepts
integers or a string representing the math type.
* 0 = Simple Moving Average (SMA),
* 1 = Exponential Moving Average (EMA),
* 2 = Weighted Moving Average (WMA),
* 3 = Double Exponential Moving Average (DEMA),
* 4 = Triple Exponential Moving Average (TEMA),
* 5 = Triangular Moving Average (TRIMA),
* 6 = T3 Moving Average,
* 7 = Kaufman Adaptive Moving Average (KAMA),
* 8 = MESA Adaptive Moving Average (MAMA)
"""
# Check if it is an integer or a string
try:
value = int(matype)
if abs(value) > len(AlphaVantage._ALPHA_VANTAGE_MATH_MAP):
raise ValueError("The value {} is not supported".format(value))
except ValueError:
value = AlphaVantage._ALPHA_VANTAGE_MATH_MAP.index(matype)
return value | [
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saltstack/salt | salt/utils/openstack/neutron.py | https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/utils/openstack/neutron.py#L872-L878 | def delete_firewall_rule(self, firewall_rule):
'''
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'''
firewall_rule_id = self._find_firewall_rule_id(firewall_rule)
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bwohlberg/sporco | sporco/fista/fista.py | https://github.com/bwohlberg/sporco/blob/8946a04331106f4e39904fbdf2dc7351900baa04/sporco/fista/fista.py#L397-L407 | def proximal_step(self, grad=None):
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grad = self.eval_grad()
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globality-corp/microcosm-flask | microcosm_flask/audit.py | https://github.com/globality-corp/microcosm-flask/blob/c2eaf57f03e7d041eea343751a4a90fcc80df418/microcosm_flask/audit.py#L59-L65 | def should_skip_logging(func):
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apache/spark | python/pyspark/heapq3.py | https://github.com/apache/spark/blob/618d6bff71073c8c93501ab7392c3cc579730f0b/python/pyspark/heapq3.py#L477-L481 | def _heapify_max(x):
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alpha-xone/xbbg | xbbg/io/storage.py | https://github.com/alpha-xone/xbbg/blob/70226eb19a72a08144b5d8cea9db4913200f7bc5/xbbg/io/storage.py#L39-L134 | def ref_file(
ticker: str, fld: str, has_date=False, cache=False, ext='parq', **kwargs
) -> str:
"""
Data file location for Bloomberg reference data
Args:
ticker: ticker name
fld: field
has_date: whether add current date to data file
cache: if has_date is True, whether to load file from latest cached
ext: file extension
**kwargs: other overrides passed to ref function
Returns:
file location
Examples:
>>> import shutil
>>>
>>> os.environ['BBG_ROOT'] = ''
>>> ref_file('BLT LN Equity', fld='Crncy') == ''
True
>>> os.environ['BBG_ROOT'] = '/data/bbg'
>>> ref_file('BLT LN Equity', fld='Crncy', cache=True)
'/data/bbg/Equity/BLT LN Equity/Crncy/ovrd=None.parq'
>>> ref_file('BLT LN Equity', fld='Crncy')
''
>>> cur_dt = utils.cur_time(tz=utils.DEFAULT_TZ)
>>> ref_file(
... 'BLT LN Equity', fld='DVD_Hist_All', has_date=True, cache=True,
... ).replace(cur_dt, '[cur_date]')
'/data/bbg/Equity/BLT LN Equity/DVD_Hist_All/asof=[cur_date], ovrd=None.parq'
>>> ref_file(
... 'BLT LN Equity', fld='DVD_Hist_All', has_date=True,
... cache=True, DVD_Start_Dt='20180101',
... ).replace(cur_dt, '[cur_date]')[:-5]
'/data/bbg/Equity/BLT LN Equity/DVD_Hist_All/asof=[cur_date], DVD_Start_Dt=20180101'
>>> sample = 'asof=2018-11-02, DVD_Start_Dt=20180101, DVD_End_Dt=20180501.pkl'
>>> root_path = 'xbbg/tests/data'
>>> sub_path = f'{root_path}/Equity/AAPL US Equity/DVD_Hist_All'
>>> os.environ['BBG_ROOT'] = root_path
>>> for tmp_file in files.all_files(sub_path): os.remove(tmp_file)
>>> files.create_folder(sub_path)
>>> sample in shutil.copy(f'{root_path}/{sample}', sub_path)
True
>>> new_file = ref_file(
... 'AAPL US Equity', 'DVD_Hist_All', DVD_Start_Dt='20180101',
... has_date=True, cache=True, ext='pkl'
... )
>>> new_file.split('/')[-1] == f'asof={cur_dt}, DVD_Start_Dt=20180101.pkl'
True
>>> old_file = 'asof=2018-11-02, DVD_Start_Dt=20180101, DVD_End_Dt=20180501.pkl'
>>> old_full = '/'.join(new_file.split('/')[:-1] + [old_file])
>>> updated_file = old_full.replace('2018-11-02', cur_dt)
>>> updated_file in shutil.copy(old_full, updated_file)
True
>>> exist_file = ref_file(
... 'AAPL US Equity', 'DVD_Hist_All', DVD_Start_Dt='20180101',
... has_date=True, cache=True, ext='pkl'
... )
>>> exist_file == updated_file
False
>>> exist_file = ref_file(
... 'AAPL US Equity', 'DVD_Hist_All', DVD_Start_Dt='20180101',
... DVD_End_Dt='20180501', has_date=True, cache=True, ext='pkl'
... )
>>> exist_file == updated_file
True
"""
data_path = os.environ.get(assist.BBG_ROOT, '').replace('\\', '/')
if (not data_path) or (not cache): return ''
proper_ticker = ticker.replace('/', '_')
cache_days = kwargs.pop('cache_days', 10)
root = f'{data_path}/{ticker.split()[-1]}/{proper_ticker}/{fld}'
if len(kwargs) > 0: info = utils.to_str(kwargs)[1:-1].replace('|', '_')
else: info = 'ovrd=None'
# Check date info
if has_date:
cur_dt = utils.cur_time()
missing = f'{root}/asof={cur_dt}, {info}.{ext}'
to_find = re.compile(rf'{root}/asof=(.*), {info}\.pkl')
cur_files = list(filter(to_find.match, sorted(
files.all_files(path_name=root, keyword=info, ext=ext)
)))
if len(cur_files) > 0:
upd_dt = to_find.match(cur_files[-1]).group(1)
diff = pd.Timestamp('today') - pd.Timestamp(upd_dt)
if diff >= pd.Timedelta(days=cache_days): return missing
return sorted(cur_files)[-1]
else: return missing
else: return f'{root}/{info}.{ext}' | [
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ticker: ticker name
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ext: file extension
**kwargs: other overrides passed to ref function
Returns:
file location
Examples:
>>> import shutil
>>>
>>> os.environ['BBG_ROOT'] = ''
>>> ref_file('BLT LN Equity', fld='Crncy') == ''
True
>>> os.environ['BBG_ROOT'] = '/data/bbg'
>>> ref_file('BLT LN Equity', fld='Crncy', cache=True)
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>>> ref_file('BLT LN Equity', fld='Crncy')
''
>>> cur_dt = utils.cur_time(tz=utils.DEFAULT_TZ)
>>> ref_file(
... 'BLT LN Equity', fld='DVD_Hist_All', has_date=True, cache=True,
... ).replace(cur_dt, '[cur_date]')
'/data/bbg/Equity/BLT LN Equity/DVD_Hist_All/asof=[cur_date], ovrd=None.parq'
>>> ref_file(
... 'BLT LN Equity', fld='DVD_Hist_All', has_date=True,
... cache=True, DVD_Start_Dt='20180101',
... ).replace(cur_dt, '[cur_date]')[:-5]
'/data/bbg/Equity/BLT LN Equity/DVD_Hist_All/asof=[cur_date], DVD_Start_Dt=20180101'
>>> sample = 'asof=2018-11-02, DVD_Start_Dt=20180101, DVD_End_Dt=20180501.pkl'
>>> root_path = 'xbbg/tests/data'
>>> sub_path = f'{root_path}/Equity/AAPL US Equity/DVD_Hist_All'
>>> os.environ['BBG_ROOT'] = root_path
>>> for tmp_file in files.all_files(sub_path): os.remove(tmp_file)
>>> files.create_folder(sub_path)
>>> sample in shutil.copy(f'{root_path}/{sample}', sub_path)
True
>>> new_file = ref_file(
... 'AAPL US Equity', 'DVD_Hist_All', DVD_Start_Dt='20180101',
... has_date=True, cache=True, ext='pkl'
... )
>>> new_file.split('/')[-1] == f'asof={cur_dt}, DVD_Start_Dt=20180101.pkl'
True
>>> old_file = 'asof=2018-11-02, DVD_Start_Dt=20180101, DVD_End_Dt=20180501.pkl'
>>> old_full = '/'.join(new_file.split('/')[:-1] + [old_file])
>>> updated_file = old_full.replace('2018-11-02', cur_dt)
>>> updated_file in shutil.copy(old_full, updated_file)
True
>>> exist_file = ref_file(
... 'AAPL US Equity', 'DVD_Hist_All', DVD_Start_Dt='20180101',
... has_date=True, cache=True, ext='pkl'
... )
>>> exist_file == updated_file
False
>>> exist_file = ref_file(
... 'AAPL US Equity', 'DVD_Hist_All', DVD_Start_Dt='20180101',
... DVD_End_Dt='20180501', has_date=True, cache=True, ext='pkl'
... )
>>> exist_file == updated_file
True | [
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hongtaocai/googlefinance | googlefinance/__init__.py | https://github.com/hongtaocai/googlefinance/blob/9f703d8d4e00d645320d49186eee4520341ec273/googlefinance/__init__.py#L84-L105 | def getQuotes(symbols):
'''
get real-time quotes (index, last trade price, last trade time, etc) for stocks, using google api: http://finance.google.com/finance/info?client=ig&q=symbols
Unlike python package 'yahoo-finance' (15 min delay), There is no delay for NYSE and NASDAQ stocks in 'googlefinance' package.
example:
quotes = getQuotes('AAPL')
return:
[{u'Index': u'NASDAQ', u'LastTradeWithCurrency': u'129.09', u'LastTradeDateTime': u'2015-03-02T16:04:29Z', u'LastTradePrice': u'129.09', u'Yield': u'1.46', u'LastTradeTime': u'4:04PM EST', u'LastTradeDateTimeLong': u'Mar 2, 4:04PM EST', u'Dividend': u'0.47', u'StockSymbol': u'AAPL', u'ID': u'22144'}]
quotes = getQuotes(['AAPL', 'GOOG'])
return:
[{u'Index': u'NASDAQ', u'LastTradeWithCurrency': u'129.09', u'LastTradeDateTime': u'2015-03-02T16:04:29Z', u'LastTradePrice': u'129.09', u'Yield': u'1.46', u'LastTradeTime': u'4:04PM EST', u'LastTradeDateTimeLong': u'Mar 2, 4:04PM EST', u'Dividend': u'0.47', u'StockSymbol': u'AAPL', u'ID': u'22144'}, {u'Index': u'NASDAQ', u'LastTradeWithCurrency': u'571.34', u'LastTradeDateTime': u'2015-03-02T16:04:29Z', u'LastTradePrice': u'571.34', u'Yield': u'', u'LastTradeTime': u'4:04PM EST', u'LastTradeDateTimeLong': u'Mar 2, 4:04PM EST', u'Dividend': u'', u'StockSymbol': u'GOOG', u'ID': u'304466804484872'}]
:param symbols: a single symbol or a list of stock symbols
:return: real-time quotes list
'''
if type(symbols) == type('str'):
symbols = [symbols]
content = json.loads(request(symbols))
return replaceKeys(content); | [
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Unlike python package 'yahoo-finance' (15 min delay), There is no delay for NYSE and NASDAQ stocks in 'googlefinance' package.
example:
quotes = getQuotes('AAPL')
return:
[{u'Index': u'NASDAQ', u'LastTradeWithCurrency': u'129.09', u'LastTradeDateTime': u'2015-03-02T16:04:29Z', u'LastTradePrice': u'129.09', u'Yield': u'1.46', u'LastTradeTime': u'4:04PM EST', u'LastTradeDateTimeLong': u'Mar 2, 4:04PM EST', u'Dividend': u'0.47', u'StockSymbol': u'AAPL', u'ID': u'22144'}]
quotes = getQuotes(['AAPL', 'GOOG'])
return:
[{u'Index': u'NASDAQ', u'LastTradeWithCurrency': u'129.09', u'LastTradeDateTime': u'2015-03-02T16:04:29Z', u'LastTradePrice': u'129.09', u'Yield': u'1.46', u'LastTradeTime': u'4:04PM EST', u'LastTradeDateTimeLong': u'Mar 2, 4:04PM EST', u'Dividend': u'0.47', u'StockSymbol': u'AAPL', u'ID': u'22144'}, {u'Index': u'NASDAQ', u'LastTradeWithCurrency': u'571.34', u'LastTradeDateTime': u'2015-03-02T16:04:29Z', u'LastTradePrice': u'571.34', u'Yield': u'', u'LastTradeTime': u'4:04PM EST', u'LastTradeDateTimeLong': u'Mar 2, 4:04PM EST', u'Dividend': u'', u'StockSymbol': u'GOOG', u'ID': u'304466804484872'}]
:param symbols: a single symbol or a list of stock symbols
:return: real-time quotes list | [
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ToucanToco/toucan-data-sdk | toucan_data_sdk/sdk.py | https://github.com/ToucanToco/toucan-data-sdk/blob/c3ca874e1b64f4bdcc2edda750a72d45d1561d8a/toucan_data_sdk/sdk.py#L194-L213 | def extract(data):
"""
Args:
data (str | byte):
Returns:
dict: Dict[str, DataFrame]
"""
_, tmp_file_path = tempfile.mkstemp()
try:
with open(tmp_file_path, 'wb') as tmp_file:
tmp_file.write(data)
if zipfile.is_zipfile(tmp_file_path):
return extract_zip(tmp_file_path)
else:
raise DataSdkError('Unsupported file type')
finally:
shutil.rmtree(tmp_file_path, ignore_errors=True) | [
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Returns:
dict: Dict[str, DataFrame] | [
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giancosta86/Iris | info/gianlucacosta/iris/versioning.py | https://github.com/giancosta86/Iris/blob/b3d92cca5cce3653519bd032346b211c46a57d05/info/gianlucacosta/iris/versioning.py#L117-L143 | def getFriendlyString(self):
"""
Returns the version, printed in a friendly way.
More precisely, it trims trailing zero components.
"""
if self._friendlyString is not None:
return self._friendlyString
resultComponents = [
self.getIntMajor(),
self.getIntMinor(),
self.getIntBuild(),
self.getIntRevision()
]
for i in range(len(resultComponents) - 1, -1, -1):
if resultComponents[i] == 0:
del resultComponents[i]
else:
break
result = ".".join(map(str, resultComponents))
self._friendlyString = result
return result | [
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HazyResearch/metal | metal/logging/logger.py | https://github.com/HazyResearch/metal/blob/c24e3772e25ac6d0917b8b7af4c1bcb92928f84a/metal/logging/logger.py#L180-L203 | def print_to_screen(self, metrics_dict):
"""Print all metrics in metrics_dict to screen"""
score_strings = defaultdict(list)
for split_metric, value in metrics_dict.items():
split, metric = split_metric.split("/", 1)
if isinstance(value, float):
score_strings[split].append(f"{metric}={value:0.3f}")
else:
score_strings[split].append(f"{metric}={value}")
header = f"{self.unit_total} {self.log_unit[:3]}"
if self.log_unit != "epochs":
epochs = self.example_total / self.epoch_size
header += f" ({epochs:0.2f} epo)"
string = f"[{header}]:"
if score_strings["train"]:
train_scores = f"{', '.join(score_strings['train'])}"
string += f" TRAIN:[{train_scores}]"
if score_strings["valid"]:
valid_scores = f"{', '.join(score_strings['valid'])}"
string += f" VALID:[{valid_scores}]"
print(string) | [
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persephone-tools/persephone | persephone/model.py | https://github.com/persephone-tools/persephone/blob/f94c63e4d5fe719fb1deba449b177bb299d225fb/persephone/model.py#L195-L236 | def transcribe(self, restore_model_path: Optional[str]=None) -> None:
""" Transcribes an untranscribed dataset. Similar to eval() except
no reference translation is assumed, thus no LER is calculated.
"""
saver = tf.train.Saver()
with tf.Session(config=allow_growth_config) as sess:
if restore_model_path:
saver.restore(sess, restore_model_path)
else:
if self.saved_model_path:
saver.restore(sess, self.saved_model_path)
else:
raise PersephoneException("No model to use for transcription.")
batch_gen = self.corpus_reader.untranscribed_batch_gen()
hyp_batches = []
for batch_i, batch in enumerate(batch_gen):
batch_x, batch_x_lens, feat_fn_batch = batch
feed_dict = {self.batch_x: batch_x,
self.batch_x_lens: batch_x_lens}
[dense_decoded] = sess.run([self.dense_decoded], feed_dict=feed_dict)
hyps = self.corpus_reader.human_readable(dense_decoded)
# Prepare dir for transcription
hyps_dir = os.path.join(self.exp_dir, "transcriptions")
if not os.path.isdir(hyps_dir):
os.mkdir(hyps_dir)
hyp_batches.append((hyps,feat_fn_batch))
with open(os.path.join(hyps_dir, "hyps.txt"), "w",
encoding=ENCODING) as hyps_f:
for hyp_batch, fn_batch in hyp_batches:
for hyp, fn in zip(hyp_batch, fn_batch):
print(fn, file=hyps_f)
print(" ".join(hyp), file=hyps_f)
print("", file=hyps_f) | [
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tanghaibao/goatools | goatools/godag_plot.py | https://github.com/tanghaibao/goatools/blob/407682e573a108864a79031f8ca19ee3bf377626/goatools/godag_plot.py#L226-L242 | def _get_node_text(self, goid, goobj):
"""Return a string to be printed in a GO term box."""
txt = []
# Header line: "GO:0036464 L04 D06"
txt.append(self.pltvars.fmthdr.format(
GO=goobj.id.replace("GO:", "GO"),
level=goobj.level,
depth=goobj.depth))
# GO name line: "cytoplamic ribonucleoprotein"
name = goobj.name.replace(",", "\n")
txt.append(name)
# study info line: "24 genes"
study_txt = self._get_study_txt(goid)
if study_txt is not None:
txt.append(study_txt)
# return text string
return "\n".join(txt) | [
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hydroshare/hs_restclient | hs_restclient/__init__.py | https://github.com/hydroshare/hs_restclient/blob/9cd106238b512e01ecd3e33425fe48c13b7f63d5/hs_restclient/__init__.py#L1135-L1148 | def updateReferenceURL(self, pid, name, ref_url, path=""):
"""Update a Referenced Content File (.url)
:param pid: The HydroShare ID of the resource for which the file should be updated
:param name: Filename for the referenced file
:param ref_url: url to be updated in the referenced file
:param path: Optional, defaults to contents directory if not provided. Folder path for the file to be updated in
:return: JsonResponse on success or HttpResponse with error status code on error
:raises: HydroShareNotAuthorized if user is not authorized to perform action.
:raises: HydroShareNotFound if the resource or resource file was not found.
:raises: HydroShareHTTPException if an unexpected HTTP response code is encountered.
"""
return self.updateReferencedFile(pid, path, name, ref_url) | [
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:param path: Optional, defaults to contents directory if not provided. Folder path for the file to be updated in
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:raises: HydroShareNotAuthorized if user is not authorized to perform action.
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:raises: HydroShareHTTPException if an unexpected HTTP response code is encountered. | [
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loli/medpy | medpy/metric/binary.py | https://github.com/loli/medpy/blob/95216b9e22e7ce301f0edf953ee2a2f1b6c6aee5/medpy/metric/binary.py#L118-L163 | def precision(result, reference):
"""
Precison.
Parameters
----------
result : array_like
Input data containing objects. Can be any type but will be converted
into binary: background where 0, object everywhere else.
reference : array_like
Input data containing objects. Can be any type but will be converted
into binary: background where 0, object everywhere else.
Returns
-------
precision : float
The precision between two binary datasets, here mostly binary objects in images,
which is defined as the fraction of retrieved instances that are relevant. The
precision is not symmetric.
See also
--------
:func:`recall`
Notes
-----
Not symmetric. The inverse of the precision is :func:`recall`.
High precision means that an algorithm returned substantially more relevant results than irrelevant.
References
----------
.. [1] http://en.wikipedia.org/wiki/Precision_and_recall
.. [2] http://en.wikipedia.org/wiki/Confusion_matrix#Table_of_confusion
"""
result = numpy.atleast_1d(result.astype(numpy.bool))
reference = numpy.atleast_1d(reference.astype(numpy.bool))
tp = numpy.count_nonzero(result & reference)
fp = numpy.count_nonzero(result & ~reference)
try:
precision = tp / float(tp + fp)
except ZeroDivisionError:
precision = 0.0
return precision | [
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Parameters
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reference : array_like
Input data containing objects. Can be any type but will be converted
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The precision between two binary datasets, here mostly binary objects in images,
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precision is not symmetric.
See also
--------
:func:`recall`
Notes
-----
Not symmetric. The inverse of the precision is :func:`recall`.
High precision means that an algorithm returned substantially more relevant results than irrelevant.
References
----------
.. [1] http://en.wikipedia.org/wiki/Precision_and_recall
.. [2] http://en.wikipedia.org/wiki/Confusion_matrix#Table_of_confusion | [
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hadrianl/huobi | huobitrade/utils.py | https://github.com/hadrianl/huobi/blob/bbfa2036703ee84a76d5d8e9f89c25fc8a55f2c7/huobitrade/utils.py#L272-L297 | def api_key_post(params, request_path, _async=False):
"""
from 火币demo, 构造post请求并调用post方法
:param params:
:param request_path:
:return:
"""
method = 'POST'
timestamp = datetime.datetime.utcnow().strftime('%Y-%m-%dT%H:%M:%S')
params_to_sign = {
'AccessKeyId': ACCESS_KEY,
'SignatureMethod': 'HmacSHA256',
'SignatureVersion': '2',
'Timestamp': timestamp
}
host_url = TRADE_URL
host_name = urllib.parse.urlparse(host_url).hostname
host_name = host_name.lower()
secret_sign = createSign(params_to_sign, method, host_name,
request_path, SECRET_KEY)
params_to_sign['Signature'] = secret_sign
if PRIVATE_KEY:
params_to_sign['PrivateSignature'] = createPrivateSign(secret_sign, PRIVATE_KEY)
url = host_url + request_path + '?' + urllib.parse.urlencode(params_to_sign)
return http_post_request(url, params, _async=_async) | [
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ev3dev/ev3dev-lang-python | ev3dev2/motor.py | https://github.com/ev3dev/ev3dev-lang-python/blob/afc98d35004b533dc161a01f7c966e78607d7c1e/ev3dev2/motor.py#L797-L804 | def stop(self, **kwargs):
"""
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raphaelvallat/pingouin | pingouin/pairwise.py | https://github.com/raphaelvallat/pingouin/blob/58b19fa4fffbfe09d58b456e3926a148249e4d9b/pingouin/pairwise.py#L411-L562 | def pairwise_tukey(dv=None, between=None, data=None, alpha=.05,
tail='two-sided', effsize='hedges'):
'''Pairwise Tukey-HSD post-hoc test.
Parameters
----------
dv : string
Name of column containing the dependant variable.
between: string
Name of column containing the between factor.
data : pandas DataFrame
DataFrame
alpha : float
Significance level
tail : string
Indicates whether to return the 'two-sided' or 'one-sided' p-values
effsize : string or None
Effect size type. Available methods are ::
'none' : no effect size
'cohen' : Unbiased Cohen d
'hedges' : Hedges g
'glass': Glass delta
'eta-square' : Eta-square
'odds-ratio' : Odds ratio
'AUC' : Area Under the Curve
Returns
-------
stats : DataFrame
Stats summary ::
'A' : Name of first measurement
'B' : Name of second measurement
'mean(A)' : Mean of first measurement
'mean(B)' : Mean of second measurement
'diff' : Mean difference
'SE' : Standard error
'tail' : indicate whether the p-values are one-sided or two-sided
'T' : T-values
'p-tukey' : Tukey-HSD corrected p-values
'efsize' : effect sizes
'eftype' : type of effect size
Notes
-----
Tukey HSD post-hoc is best for balanced one-way ANOVA.
It has been proven to be conservative for one-way ANOVA with unequal
sample sizes. However, it is not robust if the groups have unequal
variances, in which case the Games-Howell test is more adequate.
Tukey HSD is not valid for repeated measures ANOVA.
Note that when the sample sizes are unequal, this function actually
performs the Tukey-Kramer test (which allows for unequal sample sizes).
The T-values are defined as:
.. math::
t = \\frac{\\overline{x}_i - \\overline{x}_j}
{\\sqrt{2 \\cdot MS_w / n}}
where :math:`\\overline{x}_i` and :math:`\\overline{x}_j` are the means of
the first and second group, respectively, :math:`MS_w` the mean squares of
the error (computed using ANOVA) and :math:`n` the sample size.
If the sample sizes are unequal, the Tukey-Kramer procedure is
automatically used:
.. math::
t = \\frac{\\overline{x}_i - \\overline{x}_j}{\\sqrt{\\frac{MS_w}{n_i}
+ \\frac{MS_w}{n_j}}}
where :math:`n_i` and :math:`n_j` are the sample sizes of the first and
second group, respectively.
The p-values are then approximated using the Studentized range distribution
:math:`Q(\\sqrt2*|t_i|, r, N - r)` where :math:`r` is the total number of
groups and :math:`N` is the total sample size.
Note that the p-values might be slightly different than those obtained
using R or Matlab since the studentized range approximation is done using
the Gleason (1999) algorithm, which is more efficient and accurate than
the algorithms used in Matlab or R.
References
----------
.. [1] Tukey, John W. "Comparing individual means in the analysis of
variance." Biometrics (1949): 99-114.
.. [2] Gleason, John R. "An accurate, non-iterative approximation for
studentized range quantiles." Computational statistics & data
analysis 31.2 (1999): 147-158.
Examples
--------
Pairwise Tukey post-hocs on the pain threshold dataset.
>>> from pingouin import pairwise_tukey, read_dataset
>>> df = read_dataset('anova')
>>> pt = pairwise_tukey(dv='Pain threshold', between='Hair color', data=df)
'''
from pingouin.external.qsturng import psturng
# First compute the ANOVA
aov = anova(dv=dv, data=data, between=between, detailed=True)
df = aov.loc[1, 'DF']
ng = aov.loc[0, 'DF'] + 1
grp = data.groupby(between)[dv]
n = grp.count().values
gmeans = grp.mean().values
gvar = aov.loc[1, 'MS'] / n
# Pairwise combinations
g1, g2 = np.array(list(combinations(np.arange(ng), 2))).T
mn = gmeans[g1] - gmeans[g2]
se = np.sqrt(gvar[g1] + gvar[g2])
tval = mn / se
# Critical values and p-values
# from pingouin.external.qsturng import qsturng
# crit = qsturng(1 - alpha, ng, df) / np.sqrt(2)
pval = psturng(np.sqrt(2) * np.abs(tval), ng, df)
pval *= 0.5 if tail == 'one-sided' else 1
# Uncorrected p-values
# from scipy.stats import t
# punc = t.sf(np.abs(tval), n[g1].size + n[g2].size - 2) * 2
# Effect size
d = tval * np.sqrt(1 / n[g1] + 1 / n[g2])
ef = convert_effsize(d, 'cohen', effsize, n[g1], n[g2])
# Create dataframe
# Careful: pd.unique does NOT sort whereas numpy does
stats = pd.DataFrame({
'A': np.unique(data[between])[g1],
'B': np.unique(data[between])[g2],
'mean(A)': gmeans[g1],
'mean(B)': gmeans[g2],
'diff': mn,
'SE': np.round(se, 3),
'tail': tail,
'T': np.round(tval, 3),
# 'alpha': alpha,
# 'crit': np.round(crit, 3),
'p-tukey': pval,
'efsize': np.round(ef, 3),
'eftype': effsize,
})
return stats | [
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Parameters
----------
dv : string
Name of column containing the dependant variable.
between: string
Name of column containing the between factor.
data : pandas DataFrame
DataFrame
alpha : float
Significance level
tail : string
Indicates whether to return the 'two-sided' or 'one-sided' p-values
effsize : string or None
Effect size type. Available methods are ::
'none' : no effect size
'cohen' : Unbiased Cohen d
'hedges' : Hedges g
'glass': Glass delta
'eta-square' : Eta-square
'odds-ratio' : Odds ratio
'AUC' : Area Under the Curve
Returns
-------
stats : DataFrame
Stats summary ::
'A' : Name of first measurement
'B' : Name of second measurement
'mean(A)' : Mean of first measurement
'mean(B)' : Mean of second measurement
'diff' : Mean difference
'SE' : Standard error
'tail' : indicate whether the p-values are one-sided or two-sided
'T' : T-values
'p-tukey' : Tukey-HSD corrected p-values
'efsize' : effect sizes
'eftype' : type of effect size
Notes
-----
Tukey HSD post-hoc is best for balanced one-way ANOVA.
It has been proven to be conservative for one-way ANOVA with unequal
sample sizes. However, it is not robust if the groups have unequal
variances, in which case the Games-Howell test is more adequate.
Tukey HSD is not valid for repeated measures ANOVA.
Note that when the sample sizes are unequal, this function actually
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The T-values are defined as:
.. math::
t = \\frac{\\overline{x}_i - \\overline{x}_j}
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where :math:`\\overline{x}_i` and :math:`\\overline{x}_j` are the means of
the first and second group, respectively, :math:`MS_w` the mean squares of
the error (computed using ANOVA) and :math:`n` the sample size.
If the sample sizes are unequal, the Tukey-Kramer procedure is
automatically used:
.. math::
t = \\frac{\\overline{x}_i - \\overline{x}_j}{\\sqrt{\\frac{MS_w}{n_i}
+ \\frac{MS_w}{n_j}}}
where :math:`n_i` and :math:`n_j` are the sample sizes of the first and
second group, respectively.
The p-values are then approximated using the Studentized range distribution
:math:`Q(\\sqrt2*|t_i|, r, N - r)` where :math:`r` is the total number of
groups and :math:`N` is the total sample size.
Note that the p-values might be slightly different than those obtained
using R or Matlab since the studentized range approximation is done using
the Gleason (1999) algorithm, which is more efficient and accurate than
the algorithms used in Matlab or R.
References
----------
.. [1] Tukey, John W. "Comparing individual means in the analysis of
variance." Biometrics (1949): 99-114.
.. [2] Gleason, John R. "An accurate, non-iterative approximation for
studentized range quantiles." Computational statistics & data
analysis 31.2 (1999): 147-158.
Examples
--------
Pairwise Tukey post-hocs on the pain threshold dataset.
>>> from pingouin import pairwise_tukey, read_dataset
>>> df = read_dataset('anova')
>>> pt = pairwise_tukey(dv='Pain threshold', between='Hair color', data=df) | [
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spyder-ide/spyder | spyder/plugins/ipythonconsole/plugin.py | https://github.com/spyder-ide/spyder/blob/f76836ce1b924bcc4efd3f74f2960d26a4e528e0/spyder/plugins/ipythonconsole/plugin.py#L1096-L1104 | def get_client_for_file(self, filename):
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gitpython-developers/GitPython | git/objects/util.py | https://github.com/gitpython-developers/GitPython/blob/1f66e25c25cde2423917ee18c4704fff83b837d1/git/objects/util.py#L44-L65 | def get_object_type_by_name(object_type_name):
"""
:return: type suitable to handle the given object type name.
Use the type to create new instances.
:param object_type_name: Member of TYPES
:raise ValueError: In case object_type_name is unknown"""
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elif object_type_name == b"tag":
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elif object_type_name == b"blob":
from . import blob
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epfl-lts2/pygsp | pygsp/optimization.py | https://github.com/epfl-lts2/pygsp/blob/8ce5bde39206129287375af24fdbcd7edddca8c5/pygsp/optimization.py#L25-L96 | def prox_tv(x, gamma, G, A=None, At=None, nu=1, tol=10e-4, maxit=200, use_matrix=True):
r"""
Total Variation proximal operator for graphs.
This function computes the TV proximal operator for graphs. The TV norm
is the one norm of the gradient. The gradient is defined in the
function :meth:`pygsp.graphs.Graph.grad`.
This function requires the PyUNLocBoX to be executed.
This function solves:
:math:`sol = \min_{z} \frac{1}{2} \|x - z\|_2^2 + \gamma \|x\|_{TV}`
Parameters
----------
x: int
Input signal
gamma: ndarray
Regularization parameter
G: graph object
Graphs structure
A: lambda function
Forward operator, this parameter allows to solve the following problem:
:math:`sol = \min_{z} \frac{1}{2} \|x - z\|_2^2 + \gamma \| A x\|_{TV}`
(default = Id)
At: lambda function
Adjoint operator. (default = Id)
nu: float
Bound on the norm of the operator (default = 1)
tol: float
Stops criterion for the loop. The algorithm will stop if :
:math:`\frac{n(t) - n(t - 1)} {n(t)} < tol`
where :math:`n(t) = f(x) + 0.5 \|x-y\|_2^2` is the objective function at iteration :math:`t`
(default = :math:`10e-4`)
maxit: int
Maximum iteration. (default = 200)
use_matrix: bool
If a matrix should be used. (default = True)
Returns
-------
sol: solution
Examples
--------
"""
if A is None:
def A(x):
return x
if At is None:
def At(x):
return x
tight = 0
l1_nu = 2 * G.lmax * nu
if use_matrix:
def l1_a(x):
return G.Diff * A(x)
def l1_at(x):
return G.Diff * At(D.T * x)
else:
def l1_a(x):
return G.grad(A(x))
def l1_at(x):
return G.div(x)
functions, _ = _import_pyunlocbox()
functions.norm_l1(x, gamma, A=l1_a, At=l1_at, tight=tight, maxit=maxit, verbose=verbose, tol=tol) | [
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function :meth:`pygsp.graphs.Graph.grad`.
This function requires the PyUNLocBoX to be executed.
This function solves:
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Parameters
----------
x: int
Input signal
gamma: ndarray
Regularization parameter
G: graph object
Graphs structure
A: lambda function
Forward operator, this parameter allows to solve the following problem:
:math:`sol = \min_{z} \frac{1}{2} \|x - z\|_2^2 + \gamma \| A x\|_{TV}`
(default = Id)
At: lambda function
Adjoint operator. (default = Id)
nu: float
Bound on the norm of the operator (default = 1)
tol: float
Stops criterion for the loop. The algorithm will stop if :
:math:`\frac{n(t) - n(t - 1)} {n(t)} < tol`
where :math:`n(t) = f(x) + 0.5 \|x-y\|_2^2` is the objective function at iteration :math:`t`
(default = :math:`10e-4`)
maxit: int
Maximum iteration. (default = 200)
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Returns
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jupyter-widgets/jupyterlab-sidecar | setupbase.py | https://github.com/jupyter-widgets/jupyterlab-sidecar/blob/8889d09f1a0933e2cbee06d4874f720b075b29e8/setupbase.py#L616-L630 | def _iexplode_path(path):
"""Iterate over all the parts of a path.
Splits path recursively with os.path.split().
"""
(head, tail) = os.path.split(path)
if not head or (not tail and head == path):
if head:
yield head
if tail or not head:
yield tail
return
for p in _iexplode_path(head):
yield p
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marshmallow-code/apispec | src/apispec/yaml_utils.py | https://github.com/marshmallow-code/apispec/blob/e92ceffd12b2e392b8d199ed314bd2a7e6512dff/src/apispec/yaml_utils.py#L32-L47 | def load_yaml_from_docstring(docstring):
"""Loads YAML from docstring."""
split_lines = trim_docstring(docstring).split("\n")
# Cut YAML from rest of docstring
for index, line in enumerate(split_lines):
line = line.strip()
if line.startswith("---"):
cut_from = index
break
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return {}
yaml_string = "\n".join(split_lines[cut_from:])
yaml_string = dedent(yaml_string)
return yaml.safe_load(yaml_string) or {} | [
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Microsoft/nni | examples/trials/weight_sharing/ga_squad/attention.py | https://github.com/Microsoft/nni/blob/c7cc8db32da8d2ec77a382a55089f4e17247ce41/examples/trials/weight_sharing/ga_squad/attention.py#L106-L160 | def get_prob(self, src, tgt, mask, pre_compute, return_logits=False):
'''
:param s: [src_sequence_length, batch_size, src_dim]
:param h: [batch_size, tgt_dim] or [tgt_sequence_length, batch_size, tgt_dim]
:param mask: [src_sequence_length, batch_size]\
or [tgt_sequence_length, src_sequence_length, batch_sizse]
:param pre_compute: [src_sequence_length, batch_size, hidden_dim]
:return: [src_sequence_length, batch_size]\
or [tgt_sequence_length, src_sequence_length, batch_size]
'''
s_shape = src.get_shape().as_list()
h_shape = tgt.get_shape().as_list()
src_dim = s_shape[-1]
tgt_dim = h_shape[-1]
assert src_dim is not None, 'src dimension must be defined'
assert tgt_dim is not None, 'tgt dimension must be defined'
self._define_params(src_dim, tgt_dim)
if len(h_shape) == 2:
tgt = tf.expand_dims(tgt, 0)
if pre_compute is None:
pre_compute = self.get_pre_compute(src)
buf0 = pre_compute
buf1 = tf.tensordot(tgt, self.var['U'], axes=[[2], [0]])
buf2 = tf.tanh(tf.expand_dims(buf0, 0) + tf.expand_dims(buf1, 1))
if not self.is_vanilla:
xh1 = tgt
xh2 = tgt
s1 = src
if self.need_padding:
xh1 = tf.tensordot(xh1, self.var['V_t'], 1)
xh2 = tf.tensordot(xh2, self.var['S_t'], 1)
s1 = tf.tensordot(s1, self.var['V_s'], 1)
if not self.is_identity_transform:
xh1 = tf.tensordot(xh1, self.var['T'], 1)
xh2 = tf.tensordot(xh2, self.var['T'], 1)
buf3 = tf.expand_dims(s1, 0) * tf.expand_dims(xh1, 1)
buf3 = tf.tanh(tf.tensordot(buf3, self.var['V'], axes=[[3], [0]]))
buf = tf.reshape(tf.tanh(buf2 + buf3), shape=tf.shape(buf3))
else:
buf = buf2
v = self.var['v']
e = tf.tensordot(buf, v, [[3], [0]])
e = tf.squeeze(e, axis=[3])
tmp = tf.reshape(e + (mask - 1) * 10000.0, shape=tf.shape(e))
prob = tf.nn.softmax(tmp, 1)
if len(h_shape) == 2:
prob = tf.squeeze(prob, axis=[0])
tmp = tf.squeeze(tmp, axis=[0])
if return_logits:
return prob, tmp
return prob | [
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:param mask: [src_sequence_length, batch_size]\
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theolind/pymysensors | mqtt.py | https://github.com/theolind/pymysensors/blob/a139ab6e2f6b71ebaf37282f69bfd0f7fe6193b6/mqtt.py#L18-L20 | def publish(self, topic, payload, qos, retain):
"""Publish an MQTT message."""
self._mqttc.publish(topic, payload, qos, retain) | [
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HazyResearch/metal | metal/contrib/backends/wrapper.py | https://github.com/HazyResearch/metal/blob/c24e3772e25ac6d0917b8b7af4c1bcb92928f84a/metal/contrib/backends/wrapper.py#L190-L208 | def _build_vocab(self, sentences, markers=[]):
"""
Initalize symbol table dictionary
:param sentences:
:param markers:
:return:
"""
from snorkel.learning.pytorch.rnn.utils import SymbolTable
vocab = Counter()
for sent in sentences:
for w in sent:
vocab[w] += 1
word_dict = SymbolTable()
list(map(word_dict.get, vocab))
list(map(word_dict.get, markers))
return word_dict | [
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BernardFW/bernard | src/bernard/layers/definitions.py | https://github.com/BernardFW/bernard/blob/9c55703e5ffe5717c9fa39793df59dbfa5b4c5ab/src/bernard/layers/definitions.py#L75-L80 | async def become(self, layer_type: Type[L], request: 'Request') -> L:
"""
Transform this layer into another layer type
"""
raise ValueError('Cannot become "{}"'.format(layer_type.__name__)) | [
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pandas-dev/pandas | pandas/io/excel/_util.py | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/io/excel/_util.py#L176-L204 | def _fill_mi_header(row, control_row):
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Used for creating headers in Multiindex.
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----------
row : list
List of items in a single row.
control_row : list of bool
Helps to determine if particular column is in same parent index as the
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----------
Returns changed row and control_row
"""
last = row[0]
for i in range(1, len(row)):
if not control_row[i]:
last = row[i]
if row[i] == '' or row[i] is None:
row[i] = last
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control_row[i] = False
last = row[i]
return row, control_row | [
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UDST/urbansim | urbansim/models/regression.py | https://github.com/UDST/urbansim/blob/79f815a6503e109f50be270cee92d0f4a34f49ef/urbansim/models/regression.py#L178-L204 | def _model_fit_to_table(fit):
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Produce a pandas DataFrame of model fit results from a statsmodels
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Parameters
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fit : statsmodels.regression.linear_model.RegressionResults
Returns
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fit_parameters : pandas.DataFrame
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fit_parameters = pd.DataFrame(
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fit_parameters.rsquared = fit.rsquared
fit_parameters.rsquared_adj = fit.rsquared_adj
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robinandeer/puzzle | puzzle/utils/get_info.py | https://github.com/robinandeer/puzzle/blob/9476f05b416d3a5135d25492cb31411fdf831c58/puzzle/utils/get_info.py#L121-L139 | def get_cytoband_coord(chrom, pos):
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Args:
chrom(str): A chromosome
pos(int): The position
Returns:
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"""
chrom = chrom.strip('chr')
pos = int(pos)
result = None
logger.debug("Finding Cytoband for chrom:{0} pos:{1}".format(chrom, pos))
if chrom in CYTOBANDS:
for interval in CYTOBANDS[chrom][pos]:
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okfn/ofs | ofs/command.py | https://github.com/okfn/ofs/blob/c110cbecd7d0ae7e877963914a1a5af030cd6d45/ofs/command.py#L87-L187 | def proxy_upload(self, path, filename, content_type=None, content_encoding=None,
cb=None, num_cb=None):
"""
This is the main function that uploads. We assume the bucket
and key (== path) exists. What we do here is simple. Calculate
the headers we will need, (e.g. md5, content-type, etc). Then
we ask the self.get_proxy_config method to fill in the authentication
information and tell us which remote host we should talk to
for the upload. From there, the rest is ripped from
boto.key.Key.send_file
"""
from boto.connection import AWSAuthConnection
import mimetypes
from hashlib import md5
import base64
BufferSize = 65536 ## set to something very small to make sure
## chunking is working properly
fp = open(filename)
headers = { 'Content-Type': content_type }
if content_type is None:
content_type = mimetypes.guess_type(filename)[0] or "text/plain"
headers['Content-Type'] = content_type
if content_encoding is not None:
headers['Content-Encoding'] = content_encoding
m = md5()
fp.seek(0)
s = fp.read(BufferSize)
while s:
m.update(s)
s = fp.read(BufferSize)
self.size = fp.tell()
fp.seek(0)
self.md5 = m.hexdigest()
headers['Content-MD5'] = base64.encodestring(m.digest()).rstrip('\n')
headers['Content-Length'] = str(self.size)
headers['Expect'] = '100-Continue'
host, headers = self.get_proxy_config(headers, path)
### how to do this same thing with curl instead...
print("curl -i --trace-ascii foo.log -T %s -H %s https://%s%s" % (
filename,
" -H ".join("'%s: %s'" % (k,v) for k,v in headers.items()),
host, path
))
def sender(http_conn, method, path, data, headers):
http_conn.putrequest(method, path)
for key in headers:
http_conn.putheader(key, headers[key])
http_conn.endheaders()
fp.seek(0)
http_conn.set_debuglevel(0) ### XXX set to e.g. 4 to see what going on
if cb:
if num_cb > 2:
cb_count = self.size / BufferSize / (num_cb-2)
elif num_cb < 0:
cb_count = -1
else:
cb_count = 0
i = total_bytes = 0
cb(total_bytes, self.size)
l = fp.read(BufferSize)
while len(l) > 0:
http_conn.send(l)
if cb:
total_bytes += len(l)
i += 1
if i == cb_count or cb_count == -1:
cb(total_bytes, self.size)
i = 0
l = fp.read(BufferSize)
if cb:
cb(total_bytes, self.size)
response = http_conn.getresponse()
body = response.read()
fp.seek(0)
if response.status == 500 or response.status == 503 or \
response.getheader('location'):
# we'll try again
return response
elif response.status >= 200 and response.status <= 299:
self.etag = response.getheader('etag')
if self.etag != '"%s"' % self.md5:
raise Exception('ETag from S3 did not match computed MD5')
return response
else:
#raise provider.storage_response_error(
# response.status, response.reason, body)
raise Exception(response.status, response.reason, body)
awsc = AWSAuthConnection(host,
aws_access_key_id="key_id",
aws_secret_access_key="secret")
awsc._mexe('PUT', path, None, headers, sender=sender) | [
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warner/magic-wormhole | src/wormhole/cli/cli.py | https://github.com/warner/magic-wormhole/blob/995d3f546a33eec4f64df929848d86937d2003a7/src/wormhole/cli/cli.py#L332-L341 | def ssh_invite(ctx, code_length, user, **kwargs):
"""
Add a public-key to a ~/.ssh/authorized_keys file
"""
for name, value in kwargs.items():
setattr(ctx.obj, name, value)
from . import cmd_ssh
ctx.obj.code_length = code_length
ctx.obj.ssh_user = user
return go(cmd_ssh.invite, ctx.obj) | [
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fprimex/zdesk | zdesk/zdesk_api.py | https://github.com/fprimex/zdesk/blob/851611c13b4d530e9df31390b3ec709baf0a0188/zdesk/zdesk_api.py#L2919-L2922 | def resource_collection_create(self, data, **kwargs):
"https://developer.zendesk.com/rest_api/docs/core/resource_collections#create-a-resource-collection"
api_path = "/api/v2/resource_collections.json"
return self.call(api_path, method="POST", data=data, **kwargs) | [
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django-fluent/django-fluent-contents | fluent_contents/extensions/pluginpool.py | https://github.com/django-fluent/django-fluent-contents/blob/896f14add58471b98d7aa295b2c9e6abedec9003/fluent_contents/extensions/pluginpool.py#L113-L126 | def get_allowed_plugins(self, placeholder_slot):
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Return the plugins which are supported in the given placeholder name.
"""
# See if there is a limit imposed.
slot_config = appsettings.FLUENT_CONTENTS_PLACEHOLDER_CONFIG.get(placeholder_slot) or {}
plugins = slot_config.get('plugins')
if not plugins:
return self.get_plugins()
else:
try:
return self.get_plugins_by_name(*plugins)
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mattimck/python-exist | exist/auth.py | https://github.com/mattimck/python-exist/blob/2c4be9d176d8e8007c4e020ee7cd6263a2096abb/exist/auth.py#L138-L157 | def index(self, state, code=None, error=None):
"""
Receive a Exist response containing a verification code. Use the code
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"""
error = None
if code:
try:
auth_token = self.fetch_token(code, state)
except MissingTokenError:
error = self._fmt_failure(
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except MismatchingStateError:
error = self._fmt_failure('CSRF Warning! Mismatching state')
else:
error = self._fmt_failure('Unknown error while authenticating')
# Use a thread to shutdown cherrypy so we can return HTML first
self._shutdown_cherrypy()
return error if error else self.success_html % (auth_token) | [
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cmheisel/basecampreporting | src/basecampreporting/basecamp.py | https://github.com/cmheisel/basecampreporting/blob/88ecfc6e835608650ff6be23cbf2421d224c122b/src/basecampreporting/basecamp.py#L289-L298 | def create_comment(self, post_id, body):
"""
Create a new comment, associating it with a specific message.
"""
path = '/msg/create_comment'
req = ET.Element('request')
comment = ET.SubElement(req, 'comment')
ET.SubElement(comment, 'post-id').text = str(int(post_id))
ET.SubElement(comment, 'body').text = str(body)
return self._request(path, req) | [
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gwastro/pycbc | pycbc/workflow/core.py | https://github.com/gwastro/pycbc/blob/7a64cdd104d263f1b6ea0b01e6841837d05a4cb3/pycbc/workflow/core.py#L281-L302 | def add_ini_profile(self, cp, sec):
"""Add profile from configuration file.
Parameters
-----------
cp : ConfigParser object
The ConfigParser object holding the workflow configuration settings
sec : string
The section containing options for this job.
"""
for opt in cp.options(sec):
namespace = opt.split('|')[0]
if namespace == 'pycbc' or namespace == 'container':
continue
value = string.strip(cp.get(sec, opt))
key = opt.split('|')[1]
self.add_profile(namespace, key, value, force=True)
# Remove if Pegasus can apply this hint in the TC
if namespace == 'hints' and key == 'execution.site':
self.execution_site = value | [
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JukeboxPipeline/jukebox-core | src/jukeboxcore/addons/guerilla/guerillamgmt.py | https://github.com/JukeboxPipeline/jukebox-core/blob/bac2280ca49940355270e4b69400ce9976ab2e6f/src/jukeboxcore/addons/guerilla/guerillamgmt.py#L966-L980 | def setup_task_signals(self, ):
"""Setup the signals for the task page
:returns: None
:rtype: None
:raises: None
"""
log.debug("Setting up task page signals.")
self.task_user_view_pb.clicked.connect(self.task_view_user)
self.task_user_add_pb.clicked.connect(self.task_add_user)
self.task_user_remove_pb.clicked.connect(self.task_remove_user)
self.task_dep_view_pb.clicked.connect(self.task_view_dep)
self.task_link_view_pb.clicked.connect(self.task_view_link)
self.task_deadline_de.dateChanged.connect(self.task_save)
self.task_status_cb.currentIndexChanged.connect(self.task_save) | [
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jermnelson/flask-fedora-commons | flask_fedora_commons/__init__.py | https://github.com/jermnelson/flask-fedora-commons/blob/81cee0d8c9e79fa2bdd1a101facb9e8c0f307af4/flask_fedora_commons/__init__.py#L464-L503 | def replace(self,
entity_id,
property_name,
old_value,
value):
"""Method replaces a triple for the given entity/subject. Property
name is from the schema.org vocabulary.
Args:
entity_id(string): Unique ID of Fedora object
property_name(string): Prefix and property name i.e. schema:name
old_value(string): Literal or URI of old value
value(string): Literal or new value
"""
if not entity_id.startswith("http"):
entity_uri = '/'.join([self.base_url, self.transaction, entity_id])
else:
entity_uri = entity_id
sparql_template = Template("""$prefix
DELETE {
<$entity> $prop_name $old_value
} INSERT {
<$entity> $prop_name $new_value
} WHERE {
}""")
sparql = sparql_template.substitute(
prefix=build_prefixes(self.namespaces),
entity=entity_uri,
prop_name=property_name,
old_value=self.__value_format__(old_value),
new_value=self.__value_format__(value))
update_request = urllib.request.Request(
entity_uri,
data=sparql.encode(),
method='PATCH',
headers={'Content-Type': 'application/sparql-update'})
response = urllib.request.urlopen(update_request)
if response.code < 400:
return True
return False | [
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ecederstrand/exchangelib | exchangelib/properties.py | https://github.com/ecederstrand/exchangelib/blob/736347b337c239fcd6d592db5b29e819f753c1ba/exchangelib/properties.py#L560-L603 | def to_server_timezone(self, timezones, for_year):
"""Returns the Microsoft timezone ID corresponding to this timezone. There may not be a match at all, and there
may be multiple matches. If so, we return a random timezone ID.
:param timezones: A list of server timezones, as returned by
list(account.protocol.get_timezones(return_full_timezone_data=True))
:param for_year:
:return: A Microsoft timezone ID, as a string
"""
candidates = set()
for tz_id, tz_name, tz_periods, tz_transitions, tz_transitions_groups in timezones:
candidate = self.from_server_timezone(tz_periods, tz_transitions, tz_transitions_groups, for_year)
if candidate == self:
log.debug('Found exact candidate: %s (%s)', tz_id, tz_name)
# We prefer this timezone over anything else. Return immediately.
return tz_id
# Reduce list based on base bias and standard / daylight bias values
if candidate.bias != self.bias:
continue
if candidate.standard_time is None:
if self.standard_time is not None:
continue
else:
if self.standard_time is None:
continue
if candidate.standard_time.bias != self.standard_time.bias:
continue
if candidate.daylight_time is None:
if self.daylight_time is not None:
continue
else:
if self.daylight_time is None:
continue
if candidate.daylight_time.bias != self.daylight_time.bias:
continue
log.debug('Found candidate with matching biases: %s (%s)', tz_id, tz_name)
candidates.add(tz_id)
if not candidates:
raise ValueError('No server timezones match this timezone definition')
if len(candidates) == 1:
log.info('Could not find an exact timezone match for %s. Selecting the best candidate', self)
else:
log.warning('Could not find an exact timezone match for %s. Selecting a random candidate', self)
return candidates.pop() | [
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hhatto/autopep8 | autopep8.py | https://github.com/hhatto/autopep8/blob/fda3bb39181437b6b8a0aa0185f21ae5f14385dd/autopep8.py#L2695-L2734 | def _reflow_lines(parsed_tokens, indentation, max_line_length,
start_on_prefix_line):
"""Reflow the lines so that it looks nice."""
if unicode(parsed_tokens[0]) == 'def':
# A function definition gets indented a bit more.
continued_indent = indentation + ' ' * 2 * DEFAULT_INDENT_SIZE
else:
continued_indent = indentation + ' ' * DEFAULT_INDENT_SIZE
break_after_open_bracket = not start_on_prefix_line
lines = ReformattedLines(max_line_length)
lines.add_indent(len(indentation.lstrip('\r\n')))
if not start_on_prefix_line:
# If splitting after the opening bracket will cause the first element
# to be aligned weirdly, don't try it.
first_token = get_item(parsed_tokens, 0)
second_token = get_item(parsed_tokens, 1)
if (
first_token and second_token and
unicode(second_token)[0] == '(' and
len(indentation) + len(first_token) + 1 == len(continued_indent)
):
return None
for item in parsed_tokens:
lines.add_space_if_needed(unicode(item), equal=True)
save_continued_indent = continued_indent
if start_on_prefix_line and isinstance(item, Container):
start_on_prefix_line = False
continued_indent = ' ' * (lines.current_size() + 1)
item.reflow(lines, continued_indent, break_after_open_bracket)
continued_indent = save_continued_indent
return lines.emit() | [
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rosenbrockc/fortpy | fortpy/code.py | https://github.com/rosenbrockc/fortpy/blob/1ed0757c52d549e41d9d44bdea68cb89529293a5/fortpy/code.py#L431-L478 | def tree_find(self, symbol, origin, attribute):
"""Finds the code element corresponding to specified symbol
by searching all modules in the parser.
:arg symbol: the name of the code element to find.
:arg origin: an instance of a Module element who owns the text
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:arg attribute: one of ['dependencies', 'publics', 'members',
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#The symbol must be accessible to the origin module, otherwise
#it wouldn't compile. Start there, first looking at the origin
#itself and then the other modules that it depends on.
#Since we will be referring to this multiple times, might as
#well get a pointer to it.
oattr = origin.collection(attribute)
base = None
lorigin = None
if symbol in oattr:
base = oattr[symbol]
lorigin = origin
else:
for module in origin.dependencies:
usespec = module.split(".")
if len(usespec) > 1:
if usespec[1] == symbol:
#The dependency is to a specific element in the module,
#and it matches.
lorigin = self.get(usespec[0])
else:
lorigin = None
else:
#The dependency is to the entire module!
lorigin = self.get(usespec[0])
#If we have code for the origin, we can search for the
#actual base object that we are interested in
if lorigin is not None:
lattr = lorigin.collection(attribute)
if symbol in lattr:
base = lattr[symbol]
break
#By now, we either have the item we were after or we don't have
#code for the module it needs
return (base, lorigin) | [
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sethmlarson/virtualbox-python | virtualbox/library.py | https://github.com/sethmlarson/virtualbox-python/blob/706c8e3f6e3aee17eb06458e73cbb4bc2d37878b/virtualbox/library.py#L16853-L16869 | def create_host_only_network_interface(self):
"""Creates a new adapter for Host Only Networking.
out host_interface of type :class:`IHostNetworkInterface`
Created host interface object.
return progress of type :class:`IProgress`
Progress object to track the operation completion.
raises :class:`OleErrorInvalidarg`
Host network interface @a name already exists.
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(progress, host_interface) = self._call("createHostOnlyNetworkInterface")
progress = IProgress(progress)
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apple/turicreate | deps/src/libxml2-2.9.1/python/libxml2.py | https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/deps/src/libxml2-2.9.1/python/libxml2.py#L7153-L7160 | def validateElement(self, doc, elem):
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else: doc__o = doc._o
if elem is None: elem__o = None
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intuition-io/intuition | intuition/api/algorithm.py | https://github.com/intuition-io/intuition/blob/cd517e6b3b315a743eb4d0d0dc294e264ab913ce/intuition/api/algorithm.py#L114-L128 | def process_orders(self, orderbook):
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datadotworld/data.world-py | datadotworld/client/_swagger/apis/datasets_api.py | https://github.com/datadotworld/data.world-py/blob/ffaeb115f358731ab0b805b0c43b7ff2e3cf0a77/datadotworld/client/_swagger/apis/datasets_api.py#L282-L307 | def delete_dataset(self, owner, id, **kwargs):
"""
Delete a dataset
Permanently deletes a dataset and all data associated with it. This operation cannot be undone, although a new dataset may be created with the same id.
This method makes a synchronous HTTP request by default. To make an
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:param callback function: The callback function
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:param str id: Dataset unique identifier. For example, in the URL:[https://data.world/jonloyens/an-intro-to-dataworld-dataset](https://data.world/jonloyens/an-intro-to-dataworld-dataset), an-intro-to-dataworld-dataset is the unique identifier of the dataset. (required)
:return: SuccessMessage
If the method is called asynchronously,
returns the request thread.
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kwargs['_return_http_data_only'] = True
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brocade/pynos | pynos/versions/base/yang/ietf_netconf.py | https://github.com/brocade/pynos/blob/bd8a34e98f322de3fc06750827d8bbc3a0c00380/pynos/versions/base/yang/ietf_netconf.py#L484-L494 | def commit_input_confirmed(self, **kwargs):
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chaimleib/intervaltree | intervaltree/intervaltree.py | https://github.com/chaimleib/intervaltree/blob/ffb2b1667f8b832e89324a75a175be8440504c9d/intervaltree/intervaltree.py#L1084-L1091 | def containsi(self, begin, end, data=None):
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Shortcut for (Interval(begin, end, data) in tree).
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angr/angr | angr/storage/memory.py | https://github.com/angr/angr/blob/4e2f97d56af5419ee73bdb30482c8dd8ff5f3e40/angr/storage/memory.py#L341-L365 | def set_state(self, state):
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nvdv/vprof | vprof/stats_server.py | https://github.com/nvdv/vprof/blob/4c3ff78f8920ab10cb9c00b14143452aa09ff6bb/vprof/stats_server.py#L57-L66 | def do_GET(self):
"""Handles HTTP GET requests."""
handler = self.uri_map.get(self.path) or self._handle_other
content, content_type = handler()
compressed_content = gzip.compress(content)
self._send_response(
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jtwhite79/pyemu | pyemu/en.py | https://github.com/jtwhite79/pyemu/blob/c504d8e7a4097cec07655a6318d275739bd8148a/pyemu/en.py#L600-L611 | def copy(self):
""" overload of Ensemble.copy()
Returns
-------
ParameterEnsemble : ParameterEnsemble
"""
df = super(Ensemble,self).copy()
pe = ParameterEnsemble.from_dataframe(df=df,pst=self.pst.get())
pe.__istransformed = self.istransformed
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Clinical-Genomics/scout | scout/adapter/mongo/variant_loader.py | https://github.com/Clinical-Genomics/scout/blob/90a551e2e1653a319e654c2405c2866f93d0ebb9/scout/adapter/mongo/variant_loader.py#L491-L609 | def load_variants(self, case_obj, variant_type='clinical', category='snv',
rank_threshold=None, chrom=None, start=None, end=None,
gene_obj=None, build='37'):
"""Load variants for a case into scout.
Load the variants for a specific analysis type and category into scout.
If no region is specified, load all variants above rank score threshold
If region or gene is specified, load all variants from that region
disregarding variant rank(if not specified)
Args:
case_obj(dict): A case from the scout database
variant_type(str): 'clinical' or 'research'. Default: 'clinical'
category(str): 'snv', 'str' or 'sv'. Default: 'snv'
rank_threshold(float): Only load variants above this score. Default: 0
chrom(str): Load variants from a certain chromosome
start(int): Specify the start position
end(int): Specify the end position
gene_obj(dict): A gene object from the database
Returns:
nr_inserted(int)
"""
# We need the institute object
institute_id = self.institute(institute_id=case_obj['owner'])['_id']
nr_inserted = 0
variant_file = None
if variant_type == 'clinical':
if category == 'snv':
variant_file = case_obj['vcf_files'].get('vcf_snv')
elif category == 'sv':
variant_file = case_obj['vcf_files'].get('vcf_sv')
elif category == 'str':
LOG.debug('Attempt to load STR VCF.')
variant_file = case_obj['vcf_files'].get('vcf_str')
elif category == 'cancer':
# Currently this implies a paired tumor normal
variant_file = case_obj['vcf_files'].get('vcf_cancer')
elif variant_type == 'research':
if category == 'snv':
variant_file = case_obj['vcf_files'].get('vcf_snv_research')
elif category == 'sv':
variant_file = case_obj['vcf_files'].get('vcf_sv_research')
elif category == 'cancer':
variant_file = case_obj['vcf_files'].get('vcf_cancer_research')
if not variant_file:
raise SyntaxError("Vcf file does not seem to exist")
# Check if there are any variants in file
try:
vcf_obj = VCF(variant_file)
var = next(vcf_obj)
except StopIteration as err:
LOG.warning("Variant file %s does not include any variants", variant_file)
return nr_inserted
# We need to reload the file
vcf_obj = VCF(variant_file)
# Parse the neccessary headers from vcf file
rank_results_header = parse_rank_results_header(vcf_obj)
vep_header = parse_vep_header(vcf_obj)
# This is a dictionary to tell where ind are in vcf
individual_positions = {}
for i, ind in enumerate(vcf_obj.samples):
individual_positions[ind] = i
# Dictionary for cancer analysis
sample_info = {}
if category == 'cancer':
for ind in case_obj['individuals']:
if ind['phenotype'] == 2:
sample_info[ind['individual_id']] = 'case'
else:
sample_info[ind['individual_id']] = 'control'
# Check if a region scould be uploaded
region = ""
if gene_obj:
chrom = gene_obj['chromosome']
# Add same padding as VEP
start = max(gene_obj['start'] - 5000, 0)
end = gene_obj['end'] + 5000
if chrom:
# We want to load all variants in the region regardless of rank score
rank_threshold = rank_threshold or -1000
if not (start and end):
raise SyntaxError("Specify chrom start and end")
region = "{0}:{1}-{2}".format(chrom, start, end)
else:
rank_threshold = rank_threshold or 0
variants = vcf_obj(region)
try:
nr_inserted = self._load_variants(
variants=variants,
variant_type=variant_type,
case_obj=case_obj,
individual_positions=individual_positions,
rank_threshold=rank_threshold,
institute_id=institute_id,
build=build,
rank_results_header=rank_results_header,
vep_header=vep_header,
category=category,
sample_info = sample_info
)
except Exception as error:
LOG.exception('unexpected error')
LOG.warning("Deleting inserted variants")
self.delete_variants(case_obj['_id'], variant_type)
raise error
self.update_variant_rank(case_obj, variant_type, category=category)
return nr_inserted | [
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Load the variants for a specific analysis type and category into scout.
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disregarding variant rank(if not specified)
Args:
case_obj(dict): A case from the scout database
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category(str): 'snv', 'str' or 'sv'. Default: 'snv'
rank_threshold(float): Only load variants above this score. Default: 0
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nr_inserted(int) | [
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viewflow/django-fsm | django_fsm/__init__.py | https://github.com/viewflow/django-fsm/blob/c86cd3eb949467626ffc68249ad001746333c38e/django_fsm/__init__.py#L181-L192 | def conditions_met(self, instance, state):
"""
Check if all conditions have been met
"""
transition = self.get_transition(state)
if transition is None:
return False
elif transition.conditions is None:
return True
else:
return all(map(lambda condition: condition(instance), transition.conditions)) | [
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ergoithz/browsepy | browsepy/manager.py | https://github.com/ergoithz/browsepy/blob/1612a930ef220fae507e1b152c531707e555bd92/browsepy/manager.py#L99-L127 | def import_plugin(self, plugin):
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'''
names = [
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Robpol86/libnl | example_scan_access_points.py | https://github.com/Robpol86/libnl/blob/274e9fdaa39822d06ef70b799ed4a95937a4d923/example_scan_access_points.py#L102-L118 | def callback_trigger(msg, arg):
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Positional arguments:
msg -- nl_msg class instance containing the data sent by the kernel.
arg -- mutable integer (ctypes.c_int()) to update with results.
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"""
gnlh = genlmsghdr(nlmsg_data(nlmsg_hdr(msg)))
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UCL-INGI/INGInious | base-containers/base/inginious/rst.py | https://github.com/UCL-INGI/INGInious/blob/cbda9a9c7f2b8e8eb1e6d7d51f0d18092086300c/base-containers/base/inginious/rst.py#L18-L25 | def get_imageblock(filename, format=''):
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_, extension = os.path.splitext(filename)
with open(filename, "rb") as image_file:
encoded_string = base64.b64encode(image_file.read()).decode('utf-8')
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SheffieldML/GPy | GPy/kern/src/multidimensional_integral_limits.py | https://github.com/SheffieldML/GPy/blob/54c32d79d289d622fb18b898aee65a2a431d90cf/GPy/kern/src/multidimensional_integral_limits.py#L111-L120 | def Kdiag(self, X):
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I know if I should return K_ff or K_xx. In this case we're returning K_ff!!
$K_{ff}^{post} = K_{ff} - K_{fx} K_{xx}^{-1} K_{xf}$"""
K_ff = np.ones(X.shape[0])
for i,x in enumerate(X):
for il,l in enumerate(self.lengthscale):
idx = il*2
K_ff[i] *= self.k_ff(x[idx],x[idx],l)
return K_ff * self.variances[0] | [
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hydraplatform/hydra-base | hydra_base/util/dataset_util.py | https://github.com/hydraplatform/hydra-base/blob/9251ff7946505f7a272c87837390acd1c435bc6e/hydra_base/util/dataset_util.py#L95-L165 | def _get_val(val, full=False):
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Get the value(s) of a dataset as a single value or as 1-d list of
values. In the special case of timeseries, when a check is for time-based
criteria, you can return the entire timeseries.
"""
try:
val = val.strip()
except:
pass
logging.debug("%s, type=%s", val, type(val))
if isinstance(val, float):
return val
if isinstance(val, int):
return val
if isinstance(val, np.ndarray):
return list(val)
try:
val = float(val)
return val
except:
pass
try:
val = int(val)
return val
except:
pass
if type(val) == pd.DataFrame:
if full:
return val
newval = []
values = val.values
for v in values:
newv = _get_val(v)
if type(newv) == list:
newval.extend(newv)
else:
newval.append(newv)
val = newval
elif type(val) == dict:
if full:
return val
newval = []
for v in val.values():
newv = _get_val(v)
if type(newv) == list:
newval.extend(newv)
else:
newval.append(newv)
val = newval
elif type(val) == list or type(val) == np.ndarray:
newval = []
for arr_val in val:
v = _get_val(arr_val)
newval.append(v)
val = newval
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iotile/coretools | iotileemulate/iotile/emulate/reference/controller_features/tile_manager.py | https://github.com/iotile/coretools/blob/2d794f5f1346b841b0dcd16c9d284e9bf2f3c6ec/iotileemulate/iotile/emulate/reference/controller_features/tile_manager.py#L86-L92 | def clear_to_reset(self, config_vars):
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super(TileManagerState, self).clear_to_reset(config_vars)
self.registered_tiles = self.registered_tiles[:1]
self.safe_mode = False
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thiagopbueno/rddl2tf | rddl2tf/compiler.py | https://github.com/thiagopbueno/rddl2tf/blob/f7c03d3a74d2663807c1e23e04eeed2e85166b71/rddl2tf/compiler.py#L736-L784 | def _compile_arithmetic_expression(self,
expr: Expression,
scope: Dict[str, TensorFluent],
batch_size: Optional[int] = None,
noise: Optional[List[tf.Tensor]] = None) -> TensorFluent:
'''Compile an arithmetic expression `expr` into a TensorFluent
in the given `scope` with optional batch size.
Args:
expr (:obj:`rddl2tf.expr.Expression`): A RDDL arithmetic expression.
scope (Dict[str, :obj:`rddl2tf.fluent.TensorFluent`]): A fluent scope.
batch_size (Optional[size]): The batch size.
Returns:
:obj:`rddl2tf.fluent.TensorFluent`: The compiled expression as a TensorFluent.
'''
etype = expr.etype
args = expr.args
if len(args) == 1:
etype2op = {
'+': lambda x: x,
'-': lambda x: -x
}
if etype[1] not in etype2op:
raise ValueError('Invalid binary arithmetic expression:\n{}'.format(expr))
op = etype2op[etype[1]]
x = self._compile_expression(args[0], scope, batch_size, noise)
fluent = op(x)
else:
etype2op = {
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'-': lambda x, y: x - y,
'*': lambda x, y: x * y,
'/': lambda x, y: x / y,
}
if etype[1] not in etype2op:
raise ValueError('Invalid binary arithmetic expression:\n{}'.format(expr))
op = etype2op[etype[1]]
x = self._compile_expression(args[0], scope, batch_size, noise)
y = self._compile_expression(args[1], scope, batch_size, noise)
fluent = op(x, y)
return fluent | [
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batch_size (Optional[size]): The batch size.
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saltstack/salt | salt/cloud/clouds/vmware.py | https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/cloud/clouds/vmware.py#L1664-L1688 | def list_datastore_full(kwargs=None, call=None, datastore=None):
'''
Returns a dictionary with basic information for the given datastore
CLI Example:
.. code-block:: bash
salt-cloud -f list_datastore_full my-vmware-config datastore=datastore-name
'''
if call != 'function':
raise SaltCloudSystemExit(
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if kwargs:
datastore = kwargs.get('datastore', None)
if not datastore:
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mbedmicro/pyOCD | pyocd/probe/stlink/detect/windows.py | https://github.com/mbedmicro/pyOCD/blob/41a174718a9739f3cbe785c2ba21cb7fd1310c6f/pyocd/probe/stlink/detect/windows.py#L189-L209 | def _vid_pid_path_to_usb_info(vid_pid_path):
"""! Provide the vendor ID and product ID of a device based on its entry in the registry
@return Returns {'vendor_id': '<vendor ID>', 'product': '<product ID>'}
@details If the vendor ID or product ID can't be determined, they will be returned
as None.
"""
result = {"vendor_id": None, "product_id": None}
for component in vid_pid_path.split("&"):
component_part = component.lower().split("_")
if len(component_part) != 2:
logger.debug("Unexpected VID/PID string structure %s", component)
break
if component_part[0] == "vid":
result["vendor_id"] = component_part[1]
elif component_part[0] == "pid":
result["product_id"] = component_part[1]
return result | [
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christophertbrown/bioscripts | ctbBio/rRNA_copies.py | https://github.com/christophertbrown/bioscripts/blob/83b2566b3a5745437ec651cd6cafddd056846240/ctbBio/rRNA_copies.py#L18-L29 | def rna_bases(rna_cov, scaffold, bases, line):
"""
determine if read overlaps with rna, if so count bases
"""
start = int(line[3])
stop = start + bases - 1
if scaffold not in rna_cov:
return rna_cov
for pos in rna_cov[scaffold][2]:
ol = get_overlap([start, stop], pos)
rna_cov[scaffold][0] += ol
return rna_cov | [
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StackStorm/pybind | pybind/nos/v6_0_2f/brocade_entity_rpc/__init__.py | https://github.com/StackStorm/pybind/blob/44c467e71b2b425be63867aba6e6fa28b2cfe7fb/pybind/nos/v6_0_2f/brocade_entity_rpc/__init__.py#L100-L126 | def _set_get_contained_in_ID(self, v, load=False):
"""
Setter method for get_contained_in_ID, mapped from YANG variable /brocade_entity_rpc/get_contained_in_ID (rpc)
If this variable is read-only (config: false) in the
source YANG file, then _set_get_contained_in_ID is considered as a private
method. Backends looking to populate this variable should
do so via calling thisObj._set_get_contained_in_ID() directly.
YANG Description: This is a function that returns the slot/container
name/ID, where this managed device is 'contained in'.
The managed device here, is typically 1 Rack Unit (RU)
device.
"""
if hasattr(v, "_utype"):
v = v._utype(v)
try:
t = YANGDynClass(v,base=get_contained_in_ID.get_contained_in_ID, is_leaf=True, yang_name="get-contained-in-ID", rest_name="get-contained-in-ID", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=False, extensions={u'tailf-common': {u'hidden': u'rpccmd', u'actionpoint': u'get_container_id_action_point'}}, namespace='urn:brocade.com:mgmt:brocade-entity', defining_module='brocade-entity', yang_type='rpc', is_config=True)
except (TypeError, ValueError):
raise ValueError({
'error-string': """get_contained_in_ID must be of a type compatible with rpc""",
'defined-type': "rpc",
'generated-type': """YANGDynClass(base=get_contained_in_ID.get_contained_in_ID, is_leaf=True, yang_name="get-contained-in-ID", rest_name="get-contained-in-ID", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=False, extensions={u'tailf-common': {u'hidden': u'rpccmd', u'actionpoint': u'get_container_id_action_point'}}, namespace='urn:brocade.com:mgmt:brocade-entity', defining_module='brocade-entity', yang_type='rpc', is_config=True)""",
})
self.__get_contained_in_ID = t
if hasattr(self, '_set'):
self._set() | [
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caesar0301/relogger | relogger/config_parser.py | https://github.com/caesar0301/relogger/blob/40b722ad2115ac6a179e2cc4eb0c88333f5114de/relogger/config_parser.py#L149-L154 | def _detect_loop(self):
""" detect loops in flow table, raise error if being present
"""
for source, dests in self.flowtable.items():
if source in dests:
raise conferr('Loops detected: %s --> %s' % (source, source)) | [
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fabaff/python-mystrom | pymystrom/cli.py | https://github.com/fabaff/python-mystrom/blob/86410f8952104651ef76ad37c84c29740c50551e/pymystrom/cli.py#L157-L160 | def color(ip, mac, hue, saturation, value):
"""Switch the bulb on with the given color."""
bulb = MyStromBulb(ip, mac)
bulb.set_color_hsv(hue, saturation, value) | [
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pyrogram/pyrogram | pyrogram/client/methods/bots/answer_callback_query.py | https://github.com/pyrogram/pyrogram/blob/e7258a341ba905cfa86264c22040654db732ec1c/pyrogram/client/methods/bots/answer_callback_query.py#L24-L70 | def answer_callback_query(
self,
callback_query_id: str,
text: str = None,
show_alert: bool = None,
url: str = None,
cache_time: int = 0
):
"""Use this method to send answers to callback queries sent from inline keyboards.
The answer will be displayed to the user as a notification at the top of the chat screen or as an alert.
Args:
callback_query_id (``str``):
Unique identifier for the query to be answered.
text (``str``):
Text of the notification. If not specified, nothing will be shown to the user, 0-200 characters.
show_alert (``bool``):
If true, an alert will be shown by the client instead of a notification at the top of the chat screen.
Defaults to False.
url (``str``):
URL that will be opened by the user's client.
If you have created a Game and accepted the conditions via @Botfather, specify the URL that opens your
game – note that this will only work if the query comes from a callback_game button.
Otherwise, you may use links like t.me/your_bot?start=XXXX that open your bot with a parameter.
cache_time (``int``):
The maximum amount of time in seconds that the result of the callback query may be cached client-side.
Telegram apps will support caching starting in version 3.14. Defaults to 0.
Returns:
True, on success.
Raises:
:class:`RPCError <pyrogram.RPCError>` in case of a Telegram RPC error.
"""
return self.send(
functions.messages.SetBotCallbackAnswer(
query_id=int(callback_query_id),
cache_time=cache_time,
alert=show_alert or None,
message=text,
url=url
)
) | [
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chezou/tabula-py | tabula/file_util.py | https://github.com/chezou/tabula-py/blob/e61d46ee3c93bb40396e48dac5a9493e898f561a/tabula/file_util.py#L24-L63 | def localize_file(path_or_buffer):
'''Ensure localize target file.
If the target file is remote, this function fetches into local storage.
Args:
path (str):
File path or file like object or URL of target file.
Returns:
filename (str): file name in local storage
temporary_file_flag (bool): temporary file flag
'''
path_or_buffer = _stringify_path(path_or_buffer)
if _is_url(path_or_buffer):
req = urlopen(path_or_buffer)
filename = os.path.basename(req.geturl())
if os.path.splitext(filename)[-1] is not ".pdf":
pid = os.getpid()
filename = "{0}.pdf".format(pid)
with open(filename, 'wb') as f:
shutil.copyfileobj(req, f)
return filename, True
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pid = os.getpid()
filename = "{0}.pdf".format(pid)
with open(filename, 'wb') as f:
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return filename, True
# File path case
else:
return os.path.expanduser(path_or_buffer), False | [
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saltstack/salt | salt/cloud/clouds/vmware.py | https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/cloud/clouds/vmware.py#L3737-L3811 | def create_folder(kwargs=None, call=None):
'''
Create the specified folder path in this VMware environment
.. note::
To create a Host and Cluster Folder under a Datacenter, specify
``path="/yourDatacenterName/host/yourFolderName"``
To create a Network Folder under a Datacenter, specify
``path="/yourDatacenterName/network/yourFolderName"``
To create a Storage Folder under a Datacenter, specify
``path="/yourDatacenterName/datastore/yourFolderName"``
To create a VM and Template Folder under a Datacenter, specify
``path="/yourDatacenterName/vm/yourFolderName"``
CLI Example:
.. code-block:: bash
salt-cloud -f create_folder my-vmware-config path="/Local/a/b/c"
salt-cloud -f create_folder my-vmware-config path="/MyDatacenter/vm/MyVMFolder"
salt-cloud -f create_folder my-vmware-config path="/MyDatacenter/host/MyHostFolder"
salt-cloud -f create_folder my-vmware-config path="/MyDatacenter/network/MyNetworkFolder"
salt-cloud -f create_folder my-vmware-config path="/MyDatacenter/storage/MyStorageFolder"
'''
if call != 'function':
raise SaltCloudSystemExit(
'The create_folder function must be called with '
'-f or --function.'
)
# Get the service instance object
si = _get_si()
folder_path = kwargs.get('path') if kwargs and 'path' in kwargs else None
if not folder_path:
raise SaltCloudSystemExit(
'You must specify a non empty folder path.'
)
folder_refs = []
inventory_path = '/'
path_exists = True
# Split the path in a list and loop over it to check for its existence
for index, folder_name in enumerate(os.path.normpath(folder_path.strip('/')).split('/')):
inventory_path = os.path.join(inventory_path, folder_name)
folder_ref = si.content.searchIndex.FindByInventoryPath(inventoryPath=inventory_path)
if isinstance(folder_ref, vim.Folder):
# This is a folder that exists so just append and skip it
log.debug("Path %s/ exists in the inventory", inventory_path)
folder_refs.append(folder_ref)
elif isinstance(folder_ref, vim.Datacenter):
# This is a datacenter that exists so just append and skip it
log.debug("Path %s/ exists in the inventory", inventory_path)
folder_refs.append(folder_ref)
else:
path_exists = False
if not folder_refs:
# If this is the first folder, create it under the rootFolder
log.debug("Creating folder %s under rootFolder in the inventory", folder_name)
folder_refs.append(si.content.rootFolder.CreateFolder(folder_name))
else:
# Create the folder under the parent folder
log.debug("Creating path %s/ in the inventory", inventory_path)
folder_refs.append(folder_refs[index-1].CreateFolder(folder_name))
if path_exists:
return {inventory_path: 'specfied path already exists'}
return {inventory_path: 'created the specified path'} | [
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] | Create the specified folder path in this VMware environment
.. note::
To create a Host and Cluster Folder under a Datacenter, specify
``path="/yourDatacenterName/host/yourFolderName"``
To create a Network Folder under a Datacenter, specify
``path="/yourDatacenterName/network/yourFolderName"``
To create a Storage Folder under a Datacenter, specify
``path="/yourDatacenterName/datastore/yourFolderName"``
To create a VM and Template Folder under a Datacenter, specify
``path="/yourDatacenterName/vm/yourFolderName"``
CLI Example:
.. code-block:: bash
salt-cloud -f create_folder my-vmware-config path="/Local/a/b/c"
salt-cloud -f create_folder my-vmware-config path="/MyDatacenter/vm/MyVMFolder"
salt-cloud -f create_folder my-vmware-config path="/MyDatacenter/host/MyHostFolder"
salt-cloud -f create_folder my-vmware-config path="/MyDatacenter/network/MyNetworkFolder"
salt-cloud -f create_folder my-vmware-config path="/MyDatacenter/storage/MyStorageFolder" | [
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] | python | train |
github/octodns | octodns/provider/dyn.py | https://github.com/github/octodns/blob/65ee60491e22e6bb0a2aa08f7069c6ecf6c3fee6/octodns/provider/dyn.py#L156-L162 | def flush_zone(cls, zone_name):
'''Flushes the zone cache, if there is one'''
cls.log.debug('flush_zone: zone_name=%s', zone_name)
try:
del cls._cache[zone_name]
except KeyError:
pass | [
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DataMedSci/mcpartools | setup.py | https://github.com/DataMedSci/mcpartools/blob/84f869094d05bf70f09e8aaeca671ddaa1c56ec4/setup.py#L84-L97 | def get_version():
"""
Get project version (using versioneer)
:return: string containing version
"""
setup_versioneer()
clean_cache()
import versioneer
version = versioneer.get_version()
parsed_version = parse_version(version)
if '*@' in str(parsed_version):
import time
version += str(int(time.time()))
return version | [
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brentp/cruzdb | cruzdb/models.py | https://github.com/brentp/cruzdb/blob/9068d46e25952f4a929dde0242beb31fa4c7e89a/cruzdb/models.py#L527-L542 | def sequence(self, per_exon=False):
"""
Return the sequence for this feature.
if per-exon is True, return an array of exon sequences
This sequence is never reverse complemented
"""
db = self.db
if not per_exon:
start = self.txStart + 1
return _sequence(db, self.chrom, start, self.txEnd)
else:
# TODO: use same strategy as cds_sequence to reduce # of requests.
seqs = []
for start, end in self.exons:
seqs.append(_sequence(db, self.chrom, start + 1, end))
return seqs | [
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buildbot/buildbot | master/buildbot/steps/package/deb/lintian.py | https://github.com/buildbot/buildbot/blob/5df3cfae6d760557d99156633c32b1822a1e130c/master/buildbot/steps/package/deb/lintian.py#L84-L98 | def createSummary(self, log):
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Create nice summary logs.
@param log: log to create summary off of.
"""
warnings = self.obs.warnings
errors = self.obs.errors
if warnings:
self.addCompleteLog('%d Warnings' % len(warnings), "\n".join(warnings))
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stevearc/dql | dql/output.py | https://github.com/stevearc/dql/blob/e9d3aa22873076dae5ebd02e35318aa996b1e56a/dql/output.py#L249-L253 | def wait(self):
""" Block for user input """
self._write_footer()
super(ColumnFormat, self).wait()
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mar10/wsgidav | wsgidav/util.py | https://github.com/mar10/wsgidav/blob/cec0d84222fc24bea01be1cea91729001963f172/wsgidav/util.py#L246-L257 | def get_module_logger(moduleName, defaultToVerbose=False):
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@see: unit.init_logging
"""
# moduleName = moduleName.split(".")[-1]
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PaulHancock/Aegean | AegeanTools/fitting.py | https://github.com/PaulHancock/Aegean/blob/185d2b4a51b48441a1df747efc9a5271c79399fd/AegeanTools/fitting.py#L760-L792 | def bias_correct(params, data, acf=None):
"""
Calculate and apply a bias correction to the given fit parameters
Parameters
----------
params : lmfit.Parameters
The model parameters. These will be modified.
data : 2d-array
The data which was used in the fitting
acf : 2d-array
ACF of the data. Default = None.
Returns
-------
None
See Also
--------
:func:`AegeanTools.fitting.RB_bias`
"""
bias = RB_bias(data, params, acf=acf)
i = 0
for p in params:
if 'theta' in p:
continue
if params[p].vary:
params[p].value -= bias[i]
i += 1
return | [
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PmagPy/PmagPy | dialogs/pmag_er_magic_dialogs.py | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/dialogs/pmag_er_magic_dialogs.py#L1131-L1142 | def onLeftClickLabel(self, event):
"""
When user clicks on a grid label, determine if it is a row label or a col label.
Pass along the event to the appropriate function.
(It will either highlight a column for editing all values, or highlight a row for deletion).
"""
if event.Col == -1 and event.Row == -1:
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self.onSelectRow(event)
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self.drop_down_menu.on_label_click(event) | [
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senaite/senaite.core | bika/lims/browser/header_table.py | https://github.com/senaite/senaite.core/blob/7602ce2ea2f9e81eb34e20ce17b98a3e70713f85/bika/lims/browser/header_table.py#L164-L203 | def get_field_visibility_mode(self, field):
"""Returns "view" or "edit" modes, together with the place within where
this field has to be rendered, based on the permissions the current
user has for the context and the field passed in
"""
fallback_mode = ("hidden", "hidden")
widget = field.widget
# TODO This needs to be done differently
# Check where the field has to be located
layout = widget.isVisible(self.context, "header_table")
if layout in ["invisible", "hidden"]:
return fallback_mode
# Check permissions. We want to display field (either in view or edit
# modes) only if the current user has enough privileges.
if field.checkPermission("edit", self.context):
mode = "edit"
sm = getSecurityManager()
if not sm.checkPermission(ModifyPortalContent, self.context):
logger.warn("Permission '{}' granted for the edition of '{}', "
"but 'Modify portal content' not granted"
.format(field.write_permission, field.getName()))
elif field.checkPermission("view", self.context):
mode = "view"
else:
return fallback_mode
# Check if the field needs to be displayed or not, even if the user has
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if widget.isVisible(self.context, mode, field=field) != "visible":
if mode == "view":
return fallback_mode
# The field cannot be rendered in edit mode, but maybe can be
# rendered in view mode.
mode = "view"
if widget.isVisible(self.context, mode, field=field) != "visible":
return fallback_mode
return (mode, layout) | [
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twitterdev/tweet_parser | tweet_parser/tweet_checking.py | https://github.com/twitterdev/tweet_parser/blob/3435de8367d36b483a6cfd8d46cc28694ee8a42e/tweet_parser/tweet_checking.py#L129-L148 | def check_tweet(tweet, validation_checking=False):
"""
Ensures a tweet is valid and determines the type of format for the tweet.
Args:
tweet (dict/Tweet): the tweet payload
validation_checking (bool): check for valid key structure in a tweet.
"""
if "id" not in tweet:
raise NotATweetError("This text has no 'id' key")
original_format = is_original_format(tweet)
if original_format:
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else:
_check_activity_streams_tweet(tweet, validation_checking=validation_checking)
return original_format | [
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kstaniek/condoor | condoor/drivers/XE.py | https://github.com/kstaniek/condoor/blob/77c054b29d4e286c1d7aca2c74dff86b805e1fae/condoor/drivers/XE.py#L34-L73 | def reload(self, reload_timeout=300, save_config=True):
"""Reload the device.
CSM_DUT#reload
System configuration has been modified. Save? [yes/no]: yes
Building configuration...
[OK]
Proceed with reload? [confirm]
"""
SAVE_CONFIG = re.compile(re.escape("System configuration has been modified. Save? [yes/no]: "))
PROCEED = re.compile(re.escape("Proceed with reload? [confirm]"))
IMAGE = re.compile("Passing control to the main image")
BOOTSTRAP = re.compile("System Bootstrap")
LOCATED = re.compile("Located .*")
RETURN = re.compile(re.escape("Press RETURN to get started!"))
response = "yes" if save_config else "no"
# 0 1 2 3 4
events = [SAVE_CONFIG, PROCEED, LOCATED, RETURN, self.username_re,
self.password_re, BOOTSTRAP, IMAGE, TIMEOUT, EOF]
# 5 6 7 8 9
transitions = [
(SAVE_CONFIG, [0], 1, partial(a_send_line, response), 60),
(PROCEED, [0, 1], 2, partial(a_send, "\r"), reload_timeout),
(LOCATED, [2], 2, a_message_callback, reload_timeout),
# if timeout try to send the reload command again
(TIMEOUT, [0], 0, partial(a_send_line, self.reload_cmd), 10),
(BOOTSTRAP, [2], -1, a_disconnect, reload_timeout),
(IMAGE, [2], 3, a_message_callback, reload_timeout),
(self.username_re, [3], -1, a_return_and_reconnect, 0),
(self.password_re, [3], -1, a_return_and_reconnect, 0),
(RETURN, [3], -1, a_return_and_reconnect, 0),
(TIMEOUT, [2], -1, a_disconnect, 0),
(EOF, [0, 1, 2, 3], -1, a_disconnect, 0)
]
fsm = FSM("IOS-RELOAD", self.device, events, transitions, timeout=10)
return fsm.run() | [
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CSM_DUT#reload
System configuration has been modified. Save? [yes/no]: yes
Building configuration...
[OK]
Proceed with reload? [confirm] | [
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] | python | train |
ymoch/apyori | apyori.py | https://github.com/ymoch/apyori/blob/8cc20a19d01b18b83e18e54aabb416c8dedabfde/apyori.py#L206-L222 | def gen_ordered_statistics(transaction_manager, record):
"""
Returns a generator of ordered statistics as OrderedStatistic instances.
Arguments:
transaction_manager -- Transactions as a TransactionManager instance.
record -- A support record as a SupportRecord instance.
"""
items = record.items
for combination_set in combinations(sorted(items), len(items) - 1):
items_base = frozenset(combination_set)
items_add = frozenset(items.difference(items_base))
confidence = (
record.support / transaction_manager.calc_support(items_base))
lift = confidence / transaction_manager.calc_support(items_add)
yield OrderedStatistic(
frozenset(items_base), frozenset(items_add), confidence, lift) | [
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ossobv/dutree | dutree/dutree.py | https://github.com/ossobv/dutree/blob/adceeeb17f9fd70a7ed9c674850d7015d820eb2a/dutree/dutree.py#L120-L124 | def app_size(self):
"Return the total apparent size, including children."
if self._nodes is None:
return self._app_size
return sum(i.app_size() for i in self._nodes) | [
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skorch-dev/skorch | skorch/net.py | https://github.com/skorch-dev/skorch/blob/5b9b8b7b7712cb6e5aaa759d9608ea6269d5bcd3/skorch/net.py#L1222-L1248 | def _get_params_for_optimizer(self, prefix, named_parameters):
"""Parse kwargs configuration for the optimizer identified by
the given prefix. Supports param group assignment using wildcards:
optimizer__lr=0.05,
optimizer__param_groups=[
('rnn*.period', {'lr': 0.3, 'momentum': 0}),
('rnn0', {'lr': 0.1}),
]
The first positional argument are the param groups.
"""
kwargs = self._get_params_for(prefix)
params = list(named_parameters)
pgroups = []
for pattern, group in kwargs.pop('param_groups', []):
matches = [i for i, (name, _) in enumerate(params) if
fnmatch.fnmatch(name, pattern)]
if matches:
p = [params.pop(i)[1] for i in reversed(matches)]
pgroups.append({'params': p, **group})
if params:
pgroups.append({'params': [p for _, p in params]})
return [pgroups], kwargs | [
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