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How to use float_clamper method in hypothesis

Best Python code snippet using hypothesis

floats.py

Source:floats.py

...88    32: 2 ** -(2 ** (8 - 1) - 2),89    64: 2 ** -(2 ** (11 - 1) - 2),90}91assert width_smallest_normals[64] == float_info.min92def make_float_clamper(93    min_float: float = 0.0,94    max_float: float = math.inf,95    allow_zero: bool = False,  # Allows +0.0 (even if minfloat > 0)96) -> Optional[Callable[[float], float]]:97    """98    Return a function that clamps positive floats into the given bounds.99    Returns None when no values are allowed (min > max and zero is not allowed).100    """101    if max_float < min_float:102        if allow_zero:103            min_float = max_float = 0.0104        else:105            return None106    range_size = min(max_float - min_float, float_info.max)107    mantissa_mask = (1 << 52) - 1108    def float_clamper(float_val: float) -> float:109        if min_float <= float_val <= max_float:110            return float_val111        if float_val == 0.0 and allow_zero:112            return float_val113        # Outside bounds; pick a new value, sampled from the allowed range,114        # using the mantissa bits.115        mant = float_to_int(float_val) & mantissa_mask116        float_val = min_float + range_size * (mant / mantissa_mask)117        # Re-enforce the bounds (just in case of floating point arithmetic error)118        return max(min_float, min(max_float, float_val))...

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