sequence stringlengths 1.19k 35k | code stringlengths 75 8.58k |
|---|---|
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '21']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'get_entries'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '9', '12', '15', '18']}; {'id': '4', 'type': 'identifier... | def get_entries(self, chemsys_formula_id_criteria, compatible_only=True,
inc_structure=None, property_data=None,
conventional_unit_cell=False, sort_by_e_above_hull=False):
params = ["run_type", "is_hubbard", "pseudo_potential", "hubbards",
"potcar_symbol... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'aos_as_list'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'self'... | def aos_as_list(self):
'''
Returns a list of atomic orbitals, sorted from lowest to highest energy
'''
return sorted(chain.from_iterable(
[self.aos[el] * int(self.composition[el]) for el in self.elements]
), key=lambda x: x[2]) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '10']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'get_dataframe'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8']}; {'id': '4', 'type': 'identifier', 'children': [], 'v... | def get_dataframe(self, sort_key="wall_time", **kwargs):
import pandas as pd
frame = pd.DataFrame(columns=AbinitTimerSection.FIELDS)
for osect in self.order_sections(sort_key):
frame = frame.append(osect.to_dict(), ignore_index=True)
frame.info = self.info
frame.cpu_... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'order_sections'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']}; {'id': '4', 'type': 'identifier', 'children': [], 'v... | def order_sections(self, key, reverse=True):
fsort = lambda s: s.__dict__[key]
return sorted(self.sections, key=fsort, reverse=reverse) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '11']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'sort_dict'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8']}; {'id': '4', 'type': 'identifier', 'children': [], 'value... | def sort_dict(d, key=None, reverse=False):
kv_items = [kv for kv in d.items()]
if key is None:
kv_items.sort(key=lambda t: t[1], reverse=reverse)
else:
kv_items.sort(key=key, reverse=reverse)
return collections.OrderedDict(kv_items) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'sort_by_efficiency'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'va... | def sort_by_efficiency(self, reverse=True):
self._confs.sort(key=lambda c: c.efficiency, reverse=reverse)
return self |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'sort_by_speedup'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value... | def sort_by_speedup(self, reverse=True):
self._confs.sort(key=lambda c: c.speedup, reverse=reverse)
return self |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'sort_by_mem_per_proc'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], '... | def sort_by_mem_per_proc(self, reverse=False):
if any(c.mem_per_proc > 0.0 for c in self):
self._confs.sort(key=lambda c: c.mem_per_proc, reverse=reverse)
return self |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'add_cohp_dict'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']}; {'id': '4', 'type': 'identifier', 'children': [], 'va... | def add_cohp_dict(self, cohp_dict, key_sort_func=None):
if key_sort_func:
keys = sorted(cohp_dict.keys(), key=key_sort_func)
else:
keys = cohp_dict.keys()
for label in keys:
self.add_cohp(label, cohp_dict[label]) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'get_line_in_facet'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'val... | def get_line_in_facet(self, facet):
lines = list(facet.outer_lines)
pt = []
prev = None
while len(lines) > 0:
if prev is None:
l = lines.pop(0)
else:
for i, l in enumerate(lines):
if prev in l:
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5', '17']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'get_classical_addresses_from_program'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', ... | def get_classical_addresses_from_program(program) -> Dict[str, List[int]]:
addresses: Dict[str, List[int]] = defaultdict(list)
flattened_addresses = {}
for instr in program:
if isinstance(instr, Measurement) and instr.classical_reg:
addresses[instr.classical_reg.name].append(instr.classi... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8', '10']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'percolate_declares'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'typed_parameter', 'children': [... | def percolate_declares(program: Program) -> Program:
declare_program = Program()
instrs_program = Program()
for instr in program:
if isinstance(instr, Declare):
declare_program += instr
else:
instrs_program += instr
p = declare_program + instrs_program
p._defi... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '25']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'text_search'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7', '10', '13', '16', '19', '22']}; {'id': '4', 'type':... | def text_search(conn, search, *, language='english', case_sensitive=False,
diacritic_sensitive=False, text_score=False, limit=0, table=None):
raise OperationError('This query is only supported when running '
'BigchainDB with MongoDB as the backend.') |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'get_utxoset_merkle_root'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'va... | def get_utxoset_merkle_root(self):
utxoset = backend.query.get_unspent_outputs(self.connection)
hashes = [
sha3_256(
'{}{}'.format(utxo['transaction_id'], utxo['output_index']).encode()
).digest() for utxo in utxoset
]
return merkleroot(sorted(hash... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '14', '22']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'log_time'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'typed_parameter', 'children': ['5', '6']... | def log_time(func: Callable[..., Any]) -> Callable[..., Any]:
def wrapper(*args, **kwargs):
start_time = time.time()
log.info("%s starting...", func.__name__.title())
ret = func(*args, **kwargs)
log.info(
"%s finished (%s)",
func.__name__.title(),
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_get_mro'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'cls'}, {... | def _get_mro(cls):
if platform.python_implementation() == "Jython":
return (cls,) + cls.__bases__
return inspect.getmro(cls) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'sorted_walk'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'dir'}... | def sorted_walk(dir):
for base, dirs, files in os.walk(dir):
dirs.sort()
files.sort()
yield base, dirs, files |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_get_all_ns_packages'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value... | def _get_all_ns_packages(self):
pkgs = self.distribution.namespace_packages or []
return sorted(flatten(map(self._pkg_names, pkgs))) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'flatten_comments'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'valu... | def flatten_comments(comments, root_level=0):
stack = comments[:]
for item in stack:
item.nested_level = root_level
retval, parent_candidates = [], {}
while stack:
item = stack.pop(0)
if isinstance(item, praw.objects.MoreComments) and item.count == 0:
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '16']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'get_domain_listing'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '9', '12', '14']}; {'id': '4', 'type': 'identifie... | def get_domain_listing(self, domain, sort='hot', period=None, *args,
**kwargs):
if sort not in ('controversial', 'hot', 'new', 'rising', 'top',
'gilded'):
raise TypeError('Invalid sort parameter.')
if period not in (None, 'all', 'day', 'hour... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '20']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'get_submission'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14', '17']}; {'id': '4', 'type': 'identifier',... | def get_submission(self, url=None, submission_id=None, comment_limit=0,
comment_sort=None, params=None):
if bool(url) == bool(submission_id):
raise TypeError('One (and only one) of id or url is required!')
if submission_id:
url = urljoin(self.config['commen... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '22']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'search'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '9', '12', '15', '18', '20']}; {'id': '4', 'type': 'identifie... | def search(self, query, subreddit=None, sort=None, syntax=None,
period=None, *args, **kwargs):
params = {'q': query}
if 'params' in kwargs:
params.update(kwargs['params'])
kwargs.pop('params')
if sort:
params['sort'] = sort
if syntax:
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_get_sorter'}, {'id': '3', 'type': 'parameters', 'children': ['4', '7']}; {'id': '4', 'type': 'default_parameter', 'children': ['5', '... | def _get_sorter(subpath='', **defaults):
@restrict_access(scope='read')
def _sorted(self, *args, **kwargs):
if not kwargs.get('params'):
kwargs['params'] = {}
for key, value in six.iteritems(defaults):
kwargs['params'].setdefault(key, value)
url = urljoin(self._ur... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_draw_banner'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'self... | def _draw_banner(self):
n_rows, n_cols = self.term.stdscr.getmaxyx()
window = self.term.stdscr.derwin(1, n_cols, self._row, 0)
window.erase()
window.bkgd(str(' '), self.term.attr('OrderBar'))
banner = docs.BANNER_SEARCH if self.content.query else self.BANNER
items = banne... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '18']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'from_url'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '9', '12', '15']}; {'id': '4', 'type': 'identifier', 'child... | def from_url(reddit_session, url, comment_limit=0, comment_sort=None,
comments_only=False, params=None):
if params is None:
params = {}
parsed = urlparse(url)
query_pairs = parse_qs(parsed.query)
get_params = dict((k, ",".join(v)) for k, v in query_pairs.item... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'set_suggested_sort'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'va... | def set_suggested_sort(self, sort='blank'):
url = self.reddit_session.config['suggested_sort']
data = {'id': self.fullname, 'sort': sort}
return self.reddit_session.request_json(url, data=data) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '7']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'is_jump_back'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']}; {'id': '4', 'type': 'identifier', 'children': [], 'val... | def is_jump_back(self, offset, extended_arg):
if self.code[offset] != self.opc.JUMP_ABSOLUTE:
return False
return offset > self.get_target(offset, extended_arg) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'is_jump_forward'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value... | def is_jump_forward(self, offset):
opname = self.get_inst(offset).opname
if opname == 'JUMP_FORWARD':
return True
if opname != 'JUMP_ABSOLUTE':
return False
return offset < self.get_target(offset) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '23']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'show_grid'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14', '17', '20']}; {'id': '4', 'type': 'identifier'... | def show_grid(data_frame,
show_toolbar=None,
precision=None,
grid_options=None,
column_options=None,
column_definitions=None,
row_edit_callback=None):
if show_toolbar is None:
show_toolbar = defaults.show_toolbar
if prec... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_eigsorted'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'c... | def _eigsorted(cov, asc=True):
eigval, eigvec = np.linalg.eigh(cov)
order = eigval.argsort()
if not asc:
order = order[::-1]
return eigval[order], eigvec[:, order] |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'sort_args'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'args'},... | def sort_args(args):
args = args.copy()
flags = [i for i in args if FLAGS_RE.match(i[1])]
for i in flags:
args.remove(i)
return args + flags |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '14']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'plot_fracs'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11']}; {'id': '4', 'type': 'identifier', 'children': [],... | def plot_fracs(self, Q=None, ax=None, fignum=None):
from ..plotting import Tango
Tango.reset()
col = Tango.nextMedium()
if ax is None:
fig = pylab.figure(fignum)
ax = fig.add_subplot(111)
if Q is None:
Q = self.Q
ticks = numpy.arange(Q)... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9', '17']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_distance_squared'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': []... | def _distance_squared(self, p2: "Point2") -> Union[int, float]:
return (self[0] - p2[0]) ** 2 + (self[1] - p2[1]) ** 2 |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'get_next_of_type'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'valu... | def get_next_of_type(self, processor_type):
with self._condition:
if processor_type not in self:
self.wait_for_registration(processor_type)
try:
processor = self[processor_type].next_processor()
except NoProcessorVacancyError:
p... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'wait_for_registration'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], ... | def wait_for_registration(self, processor_type):
with self._condition:
self._condition.wait_for(lambda: (
processor_type in self
or self._cancelled_event.is_set()))
if self._cancelled_event.is_set():
raise WaitCancelledException() |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'wait_for_vacancy'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'valu... | def wait_for_vacancy(self, processor_type):
with self._condition:
self._condition.wait_for(lambda: (
self._processor_available(processor_type)
or self._cancelled_event.is_set()))
if self._cancelled_event.is_set():
raise WaitCancelledExcepti... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_get_sorting_message'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], '... | def _get_sorting_message(request, key):
control_list = []
reverse = request.url.query.get('reverse', None)
if reverse is None:
return control_list
if reverse.lower() == "":
control_list.append(client_list_control_pb2.ClientSortControls(
reverse=Tru... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '11']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'sort_resources'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7', '8']}; {'id': '4', 'type': 'identifier', 'childr... | def sort_resources(cls, request, resources, fail_enum, header_proto=None):
if not request.sorting:
return resources
value_handlers = cls._get_handler_set(request, fail_enum, header_proto)
def sorter(resource_a, resource_b):
for handler in value_handlers:
v... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '10']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_get_handler_set'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7']}; {'id': '4', 'type': 'identifier', 'children'... | def _get_handler_set(cls, request, fail_enum, header_proto=None):
added = set()
handlers = []
for controls in request.sorting:
control_bytes = controls.SerializeToString()
if control_bytes not in added:
added.add(control_bytes)
handlers.app... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'find_write_predecessors'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': []... | def find_write_predecessors(self, address):
predecessors = set()
enclosing_writer = None
node_stream = self._tree.walk(address)
address_len = len(address)
try:
for node_address, node in node_stream:
if node is not None:
predecessors... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '10']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_get_efron_values_single'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7', '8', '9']}; {'id': '4', 'type': 'ident... | def _get_efron_values_single(self, X, T, E, weights, beta):
n, d = X.shape
hessian = np.zeros((d, d))
gradient = np.zeros((d,))
log_lik = 0
x_death_sum = np.zeros((d,))
risk_phi, tie_phi = 0, 0
risk_phi_x, tie_phi_x = np.zeros((d,)), np.zeros((d,))
risk_ph... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '10']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_get_efron_values_batch'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7', '8', '9']}; {'id': '4', 'type': 'identi... | def _get_efron_values_batch(self, X, T, E, weights, beta):
n, d = X.shape
hessian = np.zeros((d, d))
gradient = np.zeros((d,))
log_lik = 0
risk_phi, tie_phi = 0, 0
risk_phi_x, tie_phi_x = np.zeros((d,)), np.zeros((d,))
risk_phi_x_x, tie_phi_x_x = np.zeros((d, d)),... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_treeify'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'values'}... | def _treeify(values):
if len(values) == 1:
return values
tree = np.empty_like(values)
last_full_row = int(np.log2(len(values) + 1) - 1)
len_ragged_row = len(values) - (2 ** (last_full_row + 1) - 1)
if len_ragged_row > 0:
bottom_row_ix = np.s_[: 2 * len_rag... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'nearest_neighbors'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']}; {'id': '4', 'type': 'identifier', 'children': [],... | def nearest_neighbors(self, word, top_k=10):
point = self[word]
diff = self.vectors - point
distances = np.linalg.norm(diff, axis=1)
top_ids = distances.argsort()[1:top_k+1]
return [self.vocabulary.id_word[i] for i in top_ids] |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'find_range'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'v... | def find_range(values, soft_range=[]):
try:
values = np.array(values)
values = np.squeeze(values) if len(values.shape) > 1 else values
if len(soft_range):
values = np.concatenate([values, soft_range])
if values.dtype.kind == 'M':
return values.min(), values.ma... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'dimension_sort'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7']}; {'id': '4', 'type': 'identifier', 'children': [... | def dimension_sort(odict, kdims, vdims, key_index):
sortkws = {}
ndims = len(kdims)
dimensions = kdims+vdims
indexes = [(dimensions[i], int(i not in range(ndims)),
i if i in range(ndims) else i-ndims)
for i in key_index]
cached_values = {d.name: [None]+list(d.valu... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'sort_topologically'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value':... | def sort_topologically(graph):
levels_by_name = {}
names_by_level = defaultdict(list)
def add_level_to_name(name, level):
levels_by_name[name] = level
names_by_level[level].append(name)
def walk_depth_first(name):
stack = [name]
while(stack):
name = stack.pop(... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'layer_sort'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'hmap'}... | def layer_sort(hmap):
orderings = {}
for o in hmap:
okeys = [get_overlay_spec(o, k, v) for k, v in o.data.items()]
if len(okeys) == 1 and not okeys[0] in orderings:
orderings[okeys[0]] = []
else:
orderings.update({k: [] if k == v else [v] for k, v in zip(okeys[1:], okeys)})
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'arglexsort'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'arrays... | def arglexsort(arrays):
dtypes = ','.join(array.dtype.str for array in arrays)
recarray = np.empty(len(arrays[0]), dtype=dtypes)
for i, array in enumerate(arrays):
recarray['f%s' % i] = array
return recarray.argsort() |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '11']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'sort'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 's... | def sort(self, by=None, reverse=False):
if by is None:
by = self.kdims
elif not isinstance(by, list):
by = [by]
sorted_columns = self.interface.sort(self, by, reverse)
return self.clone(sorted_columns) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'glyph_order'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': '... | def glyph_order(keys, draw_order=[]):
keys = sorted(keys)
def order_fn(glyph):
matches = [item for item in draw_order if glyph.startswith(item)]
return ((draw_order.index(matches[0]), glyph) if matches else
(1e9+keys.index(glyph), glyph))
return sorted(keys, key=order_fn) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_get_coords'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': '... | def _get_coords(self, obj):
xdim, ydim = obj.dimensions(label=True)[:2]
xcoords = obj.dimension_values(xdim, False)
ycoords = obj.dimension_values(ydim, False)
grouped = obj.groupby(xdim, container_type=OrderedDict,
group_type=Dataset).values()
order... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'most_frequent_terms'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'v... | def most_frequent_terms(self, count=0):
terms = sorted(self._terms.items(), key=lambda i: -i[1])
terms = tuple(i[0] for i in terms)
if count == 0:
return terms
elif count > 0:
return terms[:count]
else:
raise ValueError(
"Only n... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'sort_values'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': '... | def sort_values(self, ascending=False):
if self.index_type is not None:
index_expr = grizzly_impl.get_field(self.expr, 0)
column_expr = grizzly_impl.get_field(self.expr, 1)
zip_expr = grizzly_impl.zip_columns([index_expr, column_expr])
result_expr = grizzly_impl.s... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '14']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'sort'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11']}; {'id': '4', 'type': 'identifier', 'children': [], 'valu... | def sort(expr, field = None, keytype=None, ascending=True):
weld_obj = WeldObject(encoder_, decoder_)
expr_var = weld_obj.update(expr)
if isinstance(expr, WeldObject):
expr_var = expr.obj_id
weld_obj.dependencies[expr_var] = expr
if field is not None:
key_str = "x.$%s" % field
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '10']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'expand_filename_pattern'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7']}; {'id': '4', 'type': 'identifier', 'ch... | def expand_filename_pattern(self, pattern, base_dir, sourcefile=None):
expandedPattern = substitute_vars([pattern], self, sourcefile)
assert len(expandedPattern) == 1
expandedPattern = expandedPattern[0]
if expandedPattern != pattern:
logging.debug("Expanded variables in expr... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'get_file_list'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'sho... | def get_file_list(shortFile):
if "://" in shortFile:
return [shortFile]
expandedFile = os.path.expandvars(os.path.expanduser(shortFile))
fileList = glob.glob(expandedFile)
if len(fileList) != 0:
fileList.sort()
else:
logging.warning("No file matches '%s'.", shortFile)
ret... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'FPS'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'nam... | def FPS(name, sort, explicit_name=None):
n = _make_name(name, sort.length, False if explicit_name is None else explicit_name, prefix='FP_')
return FP('FPS', (n, sort), variables={n}, symbolic=True, length=sort.length) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'to_fp'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 's... | def to_fp(self, sort, rm=None):
if rm is None:
rm = fp.RM.default()
return fpToFP(rm, self, sort) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '12']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'val_to_fp'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '9']}; {'id': '4', 'type': 'identifier', 'children': [], '... | def val_to_fp(self, sort, signed=True, rm=None):
if rm is None:
rm = fp.fp.RM.default()
if sort is None:
sort = fp.fp.FSort.from_size(self.length)
op = fp.fpToFP if signed else fp.fpToFPUnsigned
return op(rm, self, sort) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'sort_orbitals'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'ele... | def sort_orbitals(element_pdos):
sorted_orbitals = ['s', 'p', 'py', 'pz', 'px',
'd', 'dxy', 'dyz', 'dz2', 'dxz', 'dx2',
'f', 'f_3', 'f_2', 'f_1', 'f_0', 'f1', 'f2', 'f3']
unsorted_keys = element_pdos.keys()
sorted_keys = []
for key in sorted_orbitals:
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '4']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'find_vasprun_files'}, {'id': '3', 'type': 'parameters', 'children': []}; {'id': '4', 'type': 'block', 'children': ['5', '14', '25', '2... | def find_vasprun_files():
folders = glob.glob('split-*')
folders = sorted(folders) if folders else ['.']
filenames = []
for fol in folders:
vr_file = os.path.join(fol, 'vasprun.xml')
vr_file_gz = os.path.join(fol, 'vasprun.xml.gz')
if os.path.exists(vr_file):
filename... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'feed'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'self'},... | def feed(self, byts):
'''
Feed bytes to the unpacker and return completed objects.
Args:
byts (bytes): Bytes to unpack.
Notes:
It is intended that this function is called multiple times with
bytes from some sort of a stream, as it will unpack and retur... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '11']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'maximum_consecutive_dry_days'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8']}; {'id': '4', 'type': 'identifier', 'ch... | def maximum_consecutive_dry_days(pr, thresh='1 mm/day', freq='YS'):
r
t = utils.convert_units_to(thresh, pr, 'hydro')
group = (pr < t).resample(time=freq)
return group.apply(rl.longest_run, dim='time') |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'daily_downsampler'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'val... | def daily_downsampler(da, freq='YS'):
r
if isinstance(da.time.values[0], np.datetime64):
years = ['{:04d}'.format(y) for y in da.time.dt.year.values]
months = ['{:02d}'.format(m) for m in da.time.dt.month.values]
else:
years = ['{:04d}'.format(v.year) for v in da.time.values]
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'identify_vertex_neighbours'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children':... | def identify_vertex_neighbours(self, vertex):
simplices = self.simplices
ridx, cidx = np.where(simplices == vertex)
neighbour_array = np.unique(np.hstack([simplices[ridx]])).tolist()
neighbour_array.remove(vertex)
return neighbour_array |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '15']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'json_encode'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '9', '12']}; {'id': '4', 'type': 'identifier', 'children... | def json_encode(self, out, limit=None, sort_keys=False, indent=None):
'''Encode the results of this paged response as JSON writing to the
provided file-like `out` object. This function will iteratively read
as many pages as present, streaming the contents out as JSON.
:param file-like ou... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'quick_search'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']}; {'id': '4', 'type': 'identifier', 'children': [], 'val... | def quick_search(self, request, **kw):
'''Execute a quick search with the specified request.
:param request: see :ref:`api-search-request`
:param **kw: See Options below
:returns: :py:class:`planet.api.models.Items`
:raises planet.api.exceptions.APIException: On API error.
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'saved_search'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']}; {'id': '4', 'type': 'identifier', 'children': [], 'val... | def saved_search(self, sid, **kw):
'''Execute a saved search by search id.
:param sid string: The id of the search
:returns: :py:class:`planet.api.models.Items`
:raises planet.api.exceptions.APIException: On API error.
:Options:
* page_size (int): Size of response pages
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_sortValue_isItalic'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value'... | def _sortValue_isItalic(font):
info = font.info
styleMapStyleName = info.styleMapStyleName
if styleMapStyleName is not None and "italic" in styleMapStyleName:
return 0
if info.italicAngle not in (None, 0):
return 0
return 1 |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_sortValue_isMonospace'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'val... | def _sortValue_isMonospace(font):
if font.info.postscriptIsFixedPitch:
return 0
if not len(font):
return 1
testWidth = None
for glyph in font:
if testWidth is None:
testWidth = glyph.width
else:
if testWidth != glyph.width:
return 1... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '11']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'flair_template_sync'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7', '8', '9', '10']}; {'id': '4', 'type': 'iden... | def flair_template_sync(self, editable, limit,
static, sort, use_css, use_text):
if not use_text and not use_css:
raise Exception('At least one of use_text or use_css must be True')
sorts = ('alpha', 'size')
if sort not in sorts:
raise Exceptio... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '14']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'props'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11']}; {'id': '4', 'type': 'identifier', 'children': [], 'val... | def props(self, element=None, mode='all', deep=False):
r
element = self._parse_element(element=element)
allowed_modes = ['all', 'constants', 'models']
mode = self._parse_mode(mode=mode, allowed=allowed_modes, single=True)
if mode == 'all':
vals = set(self.keys(mode='p... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '11']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'set_residual'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8']}; {'id': '4', 'type': 'identifier', 'children': [], 'va... | def set_residual(self, pores=[], overwrite=False):
r
Ps = self._parse_indices(pores)
if overwrite:
self['pore.residual'] = False
self['pore.residual'][Ps] = True
residual = self['pore.residual']
net = self.project.network
conns = net['throat.conns']
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'results'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'self... | def results(self, Pc):
r
Psatn = self['pore.invasion_pressure'] <= Pc
Tsatn = self['throat.invasion_pressure'] <= Pc
inv_phase = {}
inv_phase['pore.occupancy'] = sp.array(Psatn, dtype=float)
inv_phase['throat.occupancy'] = sp.array(Tsatn, dtype=float)
return inv_p... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'folderitems'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'self'... | def folderitems(self):
items = BaseView.folderitems(self)
self.fill_empty_slots(items)
items = sorted(items, key=itemgetter("pos_sortkey"))
self.fill_slots_headers(items)
return items |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'resort_client_actions'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'valu... | def resort_client_actions(portal):
sorted_actions = [
"edit",
"contacts",
"view",
"analysisrequests",
"batches",
"samplepoints",
"profiles",
"templates",
"specs",
"orders",
"reports_listing"
]
type_info = portal.portal_t... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'reindex_sortable_title'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'val... | def reindex_sortable_title(portal):
catalogs = [
"bika_catalog",
"bika_setup_catalog",
"portal_catalog",
]
for catalog_name in catalogs:
logger.info("Reindexing sortable_title for {} ...".format(catalog_name))
handler = ZLogHandler(steps=100)
catalog = api.get... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '11']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'folderitems'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8']}; {'id': '4', 'type': 'identifier', 'children': [], 'val... | def folderitems(self, full_objects=False, classic=True):
bsc = getToolByName(self.context, "bika_setup_catalog")
self.an_cats = bsc(
portal_type="AnalysisCategory",
sort_on="sortable_title")
self.an_cats_order = dict([
(b.Title, "{:04}".format(a))
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '11']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'to_display_list'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8']}; {'id': '4', 'type': 'identifier', 'children': [], ... | def to_display_list(pairs, sort_by="key", allow_empty=True):
dl = DisplayList()
if isinstance(pairs, basestring):
pairs = [pairs, pairs]
for pair in pairs:
if isinstance(pair, (tuple, list)):
dl.add(*pair)
if isinstance(pair, basestring):
dl.add(*pairs)
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'sortable_title'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'in... | def sortable_title(instance):
title = plone_sortable_title(instance)
if safe_callable(title):
title = title()
return title.lower() |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'sortable_sortkey_title'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'val... | def sortable_sortkey_title(instance):
title = sortable_title(instance)
if safe_callable(title):
title = title()
sort_key = instance.getSortKey()
if sort_key is None:
sort_key = 999999
return "{:010.3f}{}".format(sort_key, title) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'sorted_analyses'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value... | def sorted_analyses(self, analyses):
analyses = sorted(analyses, key=lambda an: an.getRequestID())
def sorted_by_sortkey(objs):
return sorted(objs, key=lambda an: an.getPrioritySortkey())
current_sample_id = None
current_analyses = []
sorted_analyses = []
for ... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'get_sorted_attachments'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'val... | def get_sorted_attachments(self):
inf = float("inf")
order = self.get_attachments_order()
attachments = self.get_attachments()
def att_cmp(att1, att2):
_n1 = att1.get('UID')
_n2 = att2.get('UID')
_i1 = _n1 in order and order.index(_n1) + 1 or inf
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'get_analyses_at'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value... | def get_analyses_at(self, slot):
slot = to_int(slot)
if slot < 1:
return list()
analyses = list()
layout = self.getLayout()
for pos in layout:
layout_slot = to_int(pos['position'])
uid = pos['analysis_uid']
if layout_slot != slot or... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'rejectionOptionsList'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value... | def rejectionOptionsList(self):
"Return a sorted list with the options defined in bikasetup"
plone = getSite()
settings = plone.bika_setup
if len(settings.RejectionReasons) > 0:
reject_reasons = settings.RejectionReasons[0]
else:
return []
sorted_k... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_get_sorted_cond_keys'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], ... | def _get_sorted_cond_keys(self, keys_list):
cond_list = []
for key in keys_list:
if key.startswith('analysisservice-'):
cond_list.append(key)
cond_list.sort()
return cond_list |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_get_sorted_action_keys'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': []... | def _get_sorted_action_keys(self, keys_list):
action_list = []
for key in keys_list:
if key.startswith('action-'):
action_list.append(key)
action_list.sort()
return action_list |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'getLinkedRequests'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': ... | def getLinkedRequests(self):
rc = api.get_tool("reference_catalog")
refs = rc.getBackReferences(self, "AnalysisRequestAttachment")
ars = map(lambda ref: api.get_object_by_uid(ref.sourceUID, None), refs)
ars = filter(None, ars)
return sorted(ars, key=api.get_path, reverse=True) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'getLinkedAnalyses'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': ... | def getLinkedAnalyses(self):
refs = get_backreferences(self, "AnalysisAttachment")
ans = map(lambda uid: api.get_object_by_uid(uid, None), refs)
ans = filter(None, ans)
return sorted(ans, key=api.get_path, reverse=True) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'get_sorted_fields'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': ... | def get_sorted_fields(self):
inf = float("inf")
order = self.get_field_order()
def field_cmp(field1, field2):
_n1 = field1.getName()
_n2 = field2.getName()
_i1 = _n1 in order and order.index(_n1) + 1 or inf
_i2 = _n2 in order and order.index(_n2) +... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'resolve_sorting'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value... | def resolve_sorting(self, query):
sorting = {}
sort_on = query.get("sidx", None)
sort_on = sort_on or query.get("sort_on", None)
sort_on = sort_on == "Title" and "sortable_title" or sort_on
if sort_on:
sorting["sort_on"] = sort_on
sort_order = query.get("s... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '7']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'is_sortable_index'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']}; {'id': '4', 'type': 'identifier', 'children': [],... | def is_sortable_index(self, index_name, catalog):
index = self.get_index(index_name, catalog)
if not index:
return False
return index.meta_type in ["FieldIndex", "DateIndex"] |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'sortable_title'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value'... | def sortable_title(portal, title):
if not title:
return ''
def_charset = portal.plone_utils.getSiteEncoding()
sortabletitle = str(title.lower().strip())
sortabletitle = num_sort_regex.sub(zero_fill, sortabletitle)
for charset in [def_charset, 'latin-1', 'utf-8']:
try:
sor... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '7']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_sort_column'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']}; {'id': '4', 'type': 'identifier', 'children': [], 'val... | def _sort_column(self, column, reverse):
if tk.DISABLED in self.state():
return
l = [(self.set(child, column), child) for child in self.get_children('')]
l.sort(reverse=reverse, key=lambda x: self._column_types[column](x[0]))
for index, (val, child) in enumerate(l):
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '11']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'column'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '9']}; {'id': '4', 'type': 'identifier', 'children': [], 'val... | def column(self, column, option=None, **kw):
config = False
if option == 'type':
return self._column_types[column]
elif 'type' in kw:
config = True
self._column_types[column] = kw.pop('type')
if kw:
self._visual_drag.column(ttk.Treeview.col... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_config_sortable'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'valu... | def _config_sortable(self, sortable):
for col in self["columns"]:
command = (lambda c=col: self._sort_column(c, True)) if sortable else ""
self.heading(col, command=command)
self._sortable = sortable |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'iter_items'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']}; {'id': '4', 'type': 'identifier', 'children': [], 'value... | def iter_items(cls, repo, common_path=None):
return (r for r in cls._iter_items(repo, common_path) if r.__class__ == SymbolicReference or not r.is_detached) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '12']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'write_cache'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '9']}; {'id': '4', 'type': 'identifier', 'children': [],... | def write_cache(entries, stream, extension_data=None, ShaStreamCls=IndexFileSHA1Writer):
stream = ShaStreamCls(stream)
tell = stream.tell
write = stream.write
version = 2
write(b"DIRC")
write(pack(">LL", version, len(entries)))
for entry in entries:
beginoffset = tell()
write... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '10']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'write_tree_from_cache'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7']}; {'id': '4', 'type': 'identifier', 'chil... | def write_tree_from_cache(entries, odb, sl, si=0):
tree_items = []
tree_items_append = tree_items.append
ci = sl.start
end = sl.stop
while ci < end:
entry = entries[ci]
if entry.stage != 0:
raise UnmergedEntriesError(entry)
ci += 1
rbound = entry.path.find... |
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