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# This file is part of Hypothesis, which may be found at
# https://github.com/HypothesisWorks/hypothesis/
#
# Copyright the Hypothesis Authors.
# Individual contributors are listed in AUTHORS.rst and the git log.
#
# This Source Code Form is subject to the terms of the Mozilla Public License,
# v. 2.0. If a copy of the MPL was not distributed with this file, You can
# obtain one at https://mozilla.org/MPL/2.0/.
import math
from sys import float_info
import pytest
from hypothesis import example, given, strategies as st
from hypothesis.internal.conjecture.choice import choice_equal, choice_permitted
from hypothesis.internal.conjecture.provider_conformance import float_constraints
from hypothesis.internal.floats import (
count_between_floats,
make_float_clamper,
next_down,
next_up,
sign_aware_lte,
)
from tests.conjecture.common import float_constr
def test_can_handle_straddling_zero():
assert count_between_floats(-0.0, 0.0) == 2
@pytest.mark.parametrize(
"func,val",
[
(next_up, math.nan),
(next_up, math.inf),
(next_up, -0.0),
(next_down, math.nan),
(next_down, -math.inf),
(next_down, 0.0),
],
)
def test_next_float_equal(func, val):
if math.isnan(val):
assert math.isnan(func(val))
else:
assert func(val) == val
# exponent comparisons:
@example(float_constr(1, float_info.max), 0)
@example(float_constr(1, float_info.max), 1)
@example(float_constr(1, float_info.max), 10)
@example(float_constr(1, float_info.max), float_info.max)
@example(float_constr(1, float_info.max), math.inf)
# mantissa comparisons:
@example(float_constr(100.0001, 100.0003), 100.0001)
@example(float_constr(100.0001, 100.0003), 100.0002)
@example(float_constr(100.0001, 100.0003), 100.0003)
@example(float_constr(100.0001, 100.0003, allow_nan=False), math.nan)
@example(float_constr(0, 10, allow_nan=False), math.nan)
@example(float_constr(0, 10, allow_nan=True), math.nan)
# the branch coverage of resampling in the "out of range of smallest magnitude" case
# relies on randomness from the mantissa. try a few different values.
@example(float_constr(-4, -1, smallest_nonzero_magnitude=4), 4)
@example(float_constr(-4, -1, smallest_nonzero_magnitude=4), 5)
@example(float_constr(-4, -1, smallest_nonzero_magnitude=4), 6)
@example(float_constr(1, 4, smallest_nonzero_magnitude=4), -4)
@example(float_constr(1, 4, smallest_nonzero_magnitude=4), -5)
@example(float_constr(1, 4, smallest_nonzero_magnitude=4), -6)
@example(float_constr(-5e-324, -0.0), 3.0)
@example(float_constr(0.0, 0.0), -0.0)
@example(float_constr(-0.0, -0.0), 0.0)
@given(float_constraints(), st.floats())
def test_float_clamper(constraints, input_value):
min_value = constraints["min_value"]
max_value = constraints["max_value"]
allow_nan = constraints["allow_nan"]
smallest_nonzero_magnitude = constraints["smallest_nonzero_magnitude"]
clamper = make_float_clamper(
min_value,
max_value,
smallest_nonzero_magnitude=smallest_nonzero_magnitude,
allow_nan=allow_nan,
)
clamped = clamper(input_value)
if math.isnan(clamped):
# we should only clamp to nan if nans are allowed.
assert allow_nan
else:
# otherwise, we should have clamped to something in the permitted range.
assert sign_aware_lte(min_value, clamped)
assert sign_aware_lte(clamped, max_value)
# if input_value was permitted in the first place, then the clamped value should
# be the same as the input value.
if choice_permitted(
input_value,
{
"min_value": min_value,
"max_value": max_value,
"allow_nan": allow_nan,
"smallest_nonzero_magnitude": smallest_nonzero_magnitude,
},
):
assert choice_equal(input_value, clamped)
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