def make_generator(self, up=True):
"""Returns a generator that cycles through every combination of Ar
if up is True starts generating from the empty set to Ar, otherwise
starts generating from Ar to the empty set
"""
if up:
for i in range(len(self._Ar)+1):
for j in _combinations(self._Ar, i):
yield set(j)
else:
for i in range(len(self._Ar), -1, -1): # iterate from top to bottom
for j in _combinations(self._Ar, i):
yield set(j)
def provisionsets_combinations(provisionsets, choose0=True):
"""
The authentication security provision sets that are yielded by
combinations of given sets.
:param provisionsets:
A set of security provision sets.
:type provisionsets: ~[:class:`ProvisionSetABC`]
:param bool choose0:
Whether to include the empty choice. If true, then the empty set of
security provisions is always included in the result. Otherwise, it
is included only if *provisionsets* contains it.
:rtype: :class:`ProvisionSetABC`
"""
if choose0:
yield iter(provisionsets).next().__class__()
for combination \
in _chain(*(_combinations(provisionsets, nchoices)
for nchoices in range(1, len(provisionsets) + 1))):
yield _reduce(_or, combination)
def _is_stereogenic(atm_key):
atm_bnd_keys = atm_bnd_keys_dct[atm_key]
bnchs = [_branch(xgr, atm_key, bnd_key) for bnd_key in atm_bnd_keys]
assert len(atm_bnd_keys) in (3, 4)
_ans = not any(
_starmap(_backbone_isomorphic, _combinations(bnchs, r=2)))
return _ans
def combinations(seq, k):
""" Return j length subsequences of elements from the input iterable.
This version uses Numpy/Scipy and should be preferred over itertools. It avoids
the creation of all intermediate Python objects.
Examples
--------
>>> import numpy as np
>>> from itertools import combinations as iter_comb
>>> x = np.arange(3)
>>> c1 = combinations(x, 2)
>>> print(c1)
[[0 1]
[0 2]
[1 2]]
>>> c2 = np.array(tuple(iter_comb(x, 2)))
>>> print(c2)
[[0 1]
[0 2]
[1 2]]
"""
from itertools import combinations as _combinations, chain
from scipy.special import comb
count = comb(len(seq), k, exact=True)
res = np.fromiter(chain.from_iterable(_combinations(seq, k)),
int,
count=count * k)
return res.reshape(-1, k)
def factors(number):
'''Find all positive factors of a positive integer.'''
_prime_factors = prime_factors(number)
combinations = set()
for i in range(1, len(_prime_factors) + 1):
combinations.update(_combinations(_prime_factors, i))
return {_functools.reduce(_mul, combination) for combination in combinations}.union({1})
def powerset(iterable):
"""Generate another iterable composed of tuple that is a subset of iterable
Example:
>>> list(powerset([1,2,3]))
[(), (1,), (2,), (3,), (1, 2), (1, 3), (2, 3), (1, 2, 3)]
"""
seq = tuple(iterable)
return _chain.from_iterable(map(lambda i: _combinations(seq, i),
range(len(seq) + 1)))
def p012(min_divisors): i = 1 jump = 2 while True: prime_factors = tuple(prime_factor(i)) number_of_factors = sum(len(set(_combinations(prime_factors, i))) for i in range(1, len(prime_factors) + 1)) + 1 if number_of_factors > min_divisors: return i i += jump jump += 1
def forall(self,t="product"):
if t.startswith("pr"):
_k = list([list(i) for i in _product(self,repeat=2)])
elif t.startswith("pe"):
_k = list([list(i) for i in _permutations(self,2)])
elif t.startswith("c") and t.endswith("s"):
_k = list([list(i) for i in _combinations(self,2)])
else:
_k = list([list(i) for i in _combinations_with_replacement(self,2)])
return lzlist(_k)
def _transform_array(self, X):
d = min(X.shape[1], self._take_max_dim)
Y = _np.zeros((X.shape[0], self.dimension()), dtype=X.dtype)
Y[:, 0:
d] = X[:, 0:
d] # orig. data = products with the implicit 1 eigenfunctions
# TODO: optimize
for i in range(d):
Y[:, i + d] = X[:, i] * X[:, i] # squares
for i, (k, l) in enumerate(_combinations(range(d), 2)):
Y[:, i + 2 * d] = X[:, k] * X[:, l] # products
return Y
def connectivity_graph(geo):
""" connectivity graph
"""
syms = _symbols(geo)
xyzs = _coordinates(geo)
def _are_bonded(idx_pair):
xyz1, xyz2 = map(xyzs.__getitem__, idx_pair)
sym1, sym2 = map(syms.__getitem__, idx_pair)
dist = numpy.linalg.norm(numpy.subtract(xyz1, xyz2))
return (False if 'X' in (sym1, sym2) else
(dist < RH_BOND_MAX) if 'H' in (sym1, sym2) else
(dist < RQ_BOND_MAX))
idxs = range(len(xyzs))
bnds = list(filter(_are_bonded, _combinations(idxs, r=2)))
return _graph_from_data(atom_symbols=syms, bond_keys=bnds)
def _process_first_window(graph, tokens, split_text):
"""Sets an edges between nodes taken from first :const:`~gensim.parsing.keywords.WINDOW_SIZE`
words of `split_text` if they exist in `tokens` and `graph`, inplace.
Parameters
----------
graph : :class:~gensim.summarization.graph.Graph
Given graph.
tokens : dict
Original units (words) as keys and processed units (tokens) as values.
split_text : list of str
Splitted text.
"""
first_window = _get_first_window(split_text)
for word_a, word_b in _combinations(first_window, 2):
_set_graph_edge(graph, tokens, word_a, word_b)
def carpanlar(sayi):
asal_carpanlar = asalCarpanlar(sayi)
if len(asal_carpanlar) == 1:
return [1] + [sayi]
sonuc = [1]
for i in range(1,len(asal_carpanlar)):
for carpilcaklar in _combinations(asal_carpanlar, i):
carpim = carpilcaklar[0]
for j in range(1,i):
carpim *= carpilcaklar[j]
sonuc.append(carpim)
sonuc.append(sayi)
return sorted(tuple(set(sonuc)))
def _process_first_window(graph, tokens, split_text):
"""Sets an edges between nodes taken from first :const:`~samenvattr.parsing.keywords.WINDOW_SIZE`
words of `split_text` if they exist in `tokens` and `graph`, inplace.
Parameters
----------
graph : :class:~samenvattr.summarization.graph.Graph
Given graph.
tokens : dict
Original units (words) as keys and processed units (tokens) as values.
split_text : list of str
Splitted text.
"""
first_window = _get_first_window(split_text)
for word_a, word_b in _combinations(first_window, 2):
_set_graph_edge(graph, tokens, word_a, word_b)
def _process_first_window(graph, tokens, split_text):
first_window = _get_first_window(split_text)
for word_a, word_b in _combinations(first_window, 2):
_set_graph_edge(graph, tokens, word_a, word_b)
from ... import digest as _digest
from .. import _std as _std_http
_DIGEST_USER_OPTIONAL_TOKENS = ('qop', 'digest_algorithm', 'client_nonce',
'opaque', 'server_nonce_use_count')
_DIGEST_USER_REQUIRED_TOKENS = ('user', 'realm', 'server_nonce', 'digest_uri',
'digest')
_DIGEST_USER_TOKENSETS = \
_frozenusetset(_chain(_DIGEST_USER_REQUIRED_TOKENS, optional_tokens)
for optional_tokens
in _chain((),
*(_combinations(_DIGEST_USER_OPTIONAL_TOKENS,
n + 1)
for n
in range(len(_DIGEST_USER_OPTIONAL_TOKENS)))))
class HttpDigestClerk(_std_http.HttpStandardClerk):
"""An authentication clerk for HTTP Digest authentication"""
__metaclass__ = _abc.ABCMeta
_DIGEST_USER_OPTIONAL_TOKENS = _DIGEST_USER_OPTIONAL_TOKENS
_DIGEST_USER_REQUIRED_TOKENS = _DIGEST_USER_REQUIRED_TOKENS
_DIGEST_USER_TOKENSETS = _DIGEST_USER_TOKENSETS
def tokens_combinations(tokens_or_names):
names = tokens_names(tokens_or_names)
return _chain(*(_combinations(names, ntokens)
for ntokens in range(len(names) + 1)))
def combinations(r, it):
return _combinations(it, r)
def powerset_reverse(iterable):
seq = tuple(reversed(iterable))
return _chain.from_iterable(map(lambda i: _combinations(seq, i),
range(len(seq), 0, -1)))
def _process_first_window(graph, tokens, split_text):
first_window = _get_first_window(split_text)
for word_a, word_b in _combinations(first_window, 2):
_set_graph_edge(graph, tokens, word_a, word_b)