def sieve(*_coconut_match_to_args, **_coconut_match_to_kwargs):
_coconut_match_check = False
if (_coconut.len(_coconut_match_to_args)
== 1) and (_coconut.isinstance(_coconut_match_to_args[0],
_coconut.abc.Iterable)):
xs = _coconut.iter(_coconut_match_to_args[0])
_coconut_match_temp_0 = _coconut.tuple(
_coconut_igetitem(xs, _coconut.slice(None, 1)))
if (_coconut.len(_coconut_match_temp_0)
== 1) and (not _coconut_match_to_kwargs):
x = _coconut_match_temp_0[0]
_coconut_match_check = True
if not _coconut_match_check:
_coconut_match_err = _coconut_MatchError(
"pattern-matching failed for "
"'def sieve([x] :: xs) = [x] :: sieve(n for n in xs if n % x)'"
" in " + _coconut.repr(_coconut.repr(_coconut_match_to_args)))
_coconut_match_err.pattern = 'def sieve([x] :: xs) = [x] :: sieve(n for n in xs if n % x)'
_coconut_match_err.value = _coconut_match_to_args
raise _coconut_match_err
return _coconut_tail_call(
_coconut.itertools.chain.from_iterable,
(f()
for f in (lambda: [x], lambda: sieve((n for n in xs if n % x)))))
def quick_sort(l):
"""Sort the input iterator, using the quick sort algorithm, and without using any data until necessary."""
_coconut_match_check = False
_coconut_match_to = l
if (_coconut.isinstance(_coconut_match_to, _coconut.abc.Iterable)):
tail = _coconut.iter(_coconut_match_to)
_coconut_match_iter_0 = _coconut.tuple(_coconut_igetitem(tail, _coconut.slice(None, 1)))
if (_coconut.len(_coconut_match_iter_0) == 1):
head = _coconut_match_iter_0[0]
_coconut_match_check = True
if _coconut_match_check:
tail, tail_ = tee(tail)
_coconut_yield_from = (_coconut.itertools.chain.from_iterable((_coconut_lazy_item() for _coconut_lazy_item in (lambda: quick_sort((x for x in tail if x < head)), lambda: (head,), lambda: quick_sort((x for x in tail_ if x >= head))))))
for _coconut_yield_item in _coconut_yield_from:
yield _coconut_yield_item
def quick_sort(l):
"""Sort the input iterator using the quick sort algorithm."""
_coconut_match_to = l
_coconut_match_check = False
if _coconut.isinstance(_coconut_match_to, _coconut.abc.Iterable):
tail = _coconut.iter(_coconut_match_to)
_coconut_match_temp_0 = _coconut.tuple(_coconut_igetitem(tail, _coconut.slice(None, 1)))
if _coconut.len(_coconut_match_temp_0) == 1:
head = _coconut_match_temp_0[0]
_coconut_match_check = True
if _coconut_match_check:
tail = reiterable(tail)
left = (x for x in tail if x < head)
right = (x for x in tail if x >= head)
# By yielding nothing if the match falls through, we implicitly return an empty iterator.
# Test cases:
_coconut_yield_from = _coconut.itertools.chain.from_iterable((_coconut_func() for _coconut_func in (lambda: quick_sort(left), lambda: [head], lambda: quick_sort(right))))
for _coconut_yield_item in _coconut_yield_from:
yield _coconut_yield_item
def create_space(name, func, *args):
"""Create a hyperopt space for the given parameter."""
_coconut_case_match_to_0 = func, args
_coconut_case_match_check_0 = False
_coconut_match_set_name_choices = _coconut_sentinel
if _coconut.isinstance(_coconut_case_match_to_0, _coconut.abc.Iterable):
_coconut_match_temp_0 = _coconut.tuple(_coconut_case_match_to_0)
if (_coconut.len(_coconut_match_temp_0) == 2) and (_coconut_match_temp_0[0] == "choice") and (_coconut.isinstance(_coconut_match_temp_0[1], _coconut.abc.Sequence)) and (_coconut.len(_coconut_match_temp_0[1]) == 1):
_coconut_match_set_name_choices = _coconut_match_temp_0[1][0]
_coconut_case_match_check_0 = True
if _coconut_case_match_check_0:
if _coconut_match_set_name_choices is not _coconut_sentinel:
choices = _coconut_match_set_name_choices
if _coconut_case_match_check_0:
return hp.choice(name, choices)
if not _coconut_case_match_check_0:
_coconut_match_set_name_start = _coconut_sentinel
_coconut_match_set_name_stop = _coconut_sentinel
_coconut_match_set_name_step = _coconut_sentinel
if _coconut.isinstance(_coconut_case_match_to_0, _coconut.abc.Iterable):
_coconut_match_temp_1 = _coconut.tuple(_coconut_case_match_to_0)
if (_coconut.len(_coconut_match_temp_1) == 2) and (_coconut_match_temp_1[0] == "randrange") and (_coconut.isinstance(_coconut_match_temp_1[1], _coconut.abc.Sequence)) and (_coconut.len(_coconut_match_temp_1[1]) == 3):
_coconut_match_set_name_start = _coconut_match_temp_1[1][0]
_coconut_match_set_name_stop = _coconut_match_temp_1[1][1]
_coconut_match_set_name_step = _coconut_match_temp_1[1][2]
_coconut_case_match_check_0 = True
if _coconut_case_match_check_0:
if _coconut_match_set_name_start is not _coconut_sentinel:
start = _coconut_match_set_name_start
if _coconut_match_set_name_stop is not _coconut_sentinel:
stop = _coconut_match_set_name_stop
if _coconut_match_set_name_step is not _coconut_sentinel:
step = _coconut_match_set_name_step
if _coconut_case_match_check_0:
if step != 1:
raise ValueError("the hyperopt backend only supports a randrange step size of 1 (use bb.choice(name, range(start, stop, step)) instead)")
# despite being called randint, hp.randint is exclusive
return start + hp.randint(name, stop - start)
if not _coconut_case_match_check_0:
_coconut_match_set_name_a = _coconut_sentinel
_coconut_match_set_name_b = _coconut_sentinel
if _coconut.isinstance(_coconut_case_match_to_0, _coconut.abc.Iterable):
_coconut_match_temp_2 = _coconut.tuple(_coconut_case_match_to_0)
if (_coconut.len(_coconut_match_temp_2) == 2) and (_coconut_match_temp_2[0] == "uniform") and (_coconut.isinstance(_coconut_match_temp_2[1], _coconut.abc.Sequence)) and (_coconut.len(_coconut_match_temp_2[1]) == 2):
_coconut_match_set_name_a = _coconut_match_temp_2[1][0]
_coconut_match_set_name_b = _coconut_match_temp_2[1][1]
_coconut_case_match_check_0 = True
if _coconut_case_match_check_0:
if _coconut_match_set_name_a is not _coconut_sentinel:
a = _coconut_match_set_name_a
if _coconut_match_set_name_b is not _coconut_sentinel:
b = _coconut_match_set_name_b
if _coconut_case_match_check_0:
return hp.uniform(name, a, b)
if not _coconut_case_match_check_0:
_coconut_match_set_name_mu = _coconut_sentinel
_coconut_match_set_name_sigma = _coconut_sentinel
if _coconut.isinstance(_coconut_case_match_to_0, _coconut.abc.Iterable):
_coconut_match_temp_3 = _coconut.tuple(_coconut_case_match_to_0)
if (_coconut.len(_coconut_match_temp_3) == 2) and (_coconut_match_temp_3[0] == "normalvariate") and (_coconut.isinstance(_coconut_match_temp_3[1], _coconut.abc.Sequence)) and (_coconut.len(_coconut_match_temp_3[1]) == 2):
_coconut_match_set_name_mu = _coconut_match_temp_3[1][0]
_coconut_match_set_name_sigma = _coconut_match_temp_3[1][1]
_coconut_case_match_check_0 = True
if _coconut_case_match_check_0:
if _coconut_match_set_name_mu is not _coconut_sentinel:
mu = _coconut_match_set_name_mu
if _coconut_match_set_name_sigma is not _coconut_sentinel:
sigma = _coconut_match_set_name_sigma
if _coconut_case_match_check_0:
return hp.normal(name, mu, sigma)
raise TypeError("invalid parameter {_coconut_format_0}".format(_coconut_format_0=(name)))
def create_space(name, func, *args):
"""Create a scikit-optimize space for the given parameter."""
name = py_str(name)
_coconut_case_match_to_0 = func, args
_coconut_case_match_check_0 = False
_coconut_match_set_name_choices = _coconut_sentinel
if _coconut.isinstance(_coconut_case_match_to_0, _coconut.abc.Iterable):
_coconut_match_temp_0 = _coconut.tuple(_coconut_case_match_to_0)
if (_coconut.len(_coconut_match_temp_0)
== 2) and (_coconut_match_temp_0[0]
== "choice") and (_coconut.isinstance(
_coconut_match_temp_0[1],
_coconut.abc.Sequence)) and (_coconut.len(
_coconut_match_temp_0[1]) == 1):
_coconut_match_set_name_choices = _coconut_match_temp_0[1][0]
_coconut_case_match_check_0 = True
if _coconut_case_match_check_0:
if _coconut_match_set_name_choices is not _coconut_sentinel:
choices = _coconut_match_set_name_choices
if _coconut_case_match_check_0:
return Categorical(choices, name=name)
if not _coconut_case_match_check_0:
_coconut_match_set_name_start = _coconut_sentinel
_coconut_match_set_name_stop = _coconut_sentinel
_coconut_match_set_name_step = _coconut_sentinel
if _coconut.isinstance(_coconut_case_match_to_0,
_coconut.abc.Iterable):
_coconut_match_temp_1 = _coconut.tuple(_coconut_case_match_to_0)
if (_coconut.len(_coconut_match_temp_1)
== 2) and (_coconut_match_temp_1[0]
== "randrange") and (_coconut.isinstance(
_coconut_match_temp_1[1],
_coconut.abc.Sequence)) and (_coconut.len(
_coconut_match_temp_1[1]) == 3):
_coconut_match_set_name_start = _coconut_match_temp_1[1][0]
_coconut_match_set_name_stop = _coconut_match_temp_1[1][1]
_coconut_match_set_name_step = _coconut_match_temp_1[1][2]
_coconut_case_match_check_0 = True
if _coconut_case_match_check_0:
if _coconut_match_set_name_start is not _coconut_sentinel:
start = _coconut_match_set_name_start
if _coconut_match_set_name_stop is not _coconut_sentinel:
stop = _coconut_match_set_name_stop
if _coconut_match_set_name_step is not _coconut_sentinel:
step = _coconut_match_set_name_step
if _coconut_case_match_check_0:
if step != 1:
raise ValueError(
"the scikit-optimize backend only supports a randrange step size of 1"
)
stop -= 1 # scikit-optimize ranges are inclusive
return Integer(start, stop, name=name)
if not _coconut_case_match_check_0:
_coconut_match_set_name_a = _coconut_sentinel
_coconut_match_set_name_b = _coconut_sentinel
if _coconut.isinstance(_coconut_case_match_to_0,
_coconut.abc.Iterable):
_coconut_match_temp_2 = _coconut.tuple(_coconut_case_match_to_0)
if (_coconut.len(_coconut_match_temp_2)
== 2) and (_coconut_match_temp_2[0]
== "uniform") and (_coconut.isinstance(
_coconut_match_temp_2[1],
_coconut.abc.Sequence)) and (_coconut.len(
_coconut_match_temp_2[1]) == 2):
_coconut_match_set_name_a = _coconut_match_temp_2[1][0]
_coconut_match_set_name_b = _coconut_match_temp_2[1][1]
_coconut_case_match_check_0 = True
if _coconut_case_match_check_0:
if _coconut_match_set_name_a is not _coconut_sentinel:
a = _coconut_match_set_name_a
if _coconut_match_set_name_b is not _coconut_sentinel:
b = _coconut_match_set_name_b
if _coconut_case_match_check_0:
return Real(a, b, name=name)
raise TypeError("invalid parameter {_coconut_format_0}".format(
_coconut_format_0=(name)))