stateful test finds a bug with a tiny state

[paraseba]

FAILED tests/test_stateful_repo_ops.py::VersionControlTest::runTest - RuntimeWarning: invalid value encountered in multiply

____________________________________________________________________________________________ VersionControlTest.runTest _____________________________________________________________________________________________

self = <hypothesis.stateful.VersionControlStateMachine.TestCase testMethod=runTest>

    def runTest(self):
>       run_state_machine_as_test(cls, settings=self.settings)

../../miniconda3/envs/icechunk/lib/python3.12/site-packages/hypothesis/stateful.py:437:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
../../miniconda3/envs/icechunk/lib/python3.12/site-packages/hypothesis/stateful.py:241: in run_state_machine_as_test
    run_state_machine(state_machine_factory)
../../miniconda3/envs/icechunk/lib/python3.12/site-packages/hypothesis/stateful.py:108: in run_state_machine
    @given(st.data())
tests/test_stateful_repo_ops.py:224: in initialize
    self.set_doc(path="zarr.json", value=data.draw(v3_array_metadata()))
../../miniconda3/envs/icechunk/lib/python3.12/site-packages/hypothesis/strategies/_internal/core.py:2151: in draw
    result = self.conjecture_data.draw(strategy, observe_as=f"generate:{desc}")
../../miniconda3/envs/icechunk/lib/python3.12/site-packages/hypothesis/internal/conjecture/data.py:2503: in draw
    return strategy.do_draw(self)
../../miniconda3/envs/icechunk/lib/python3.12/site-packages/hypothesis/strategies/_internal/lazy.py:167: in do_draw
    return data.draw(self.wrapped_strategy)
../../miniconda3/envs/icechunk/lib/python3.12/site-packages/hypothesis/internal/conjecture/data.py:2503: in draw
    return strategy.do_draw(self)
../../miniconda3/envs/icechunk/lib/python3.12/site-packages/hypothesis/strategies/_internal/core.py:1775: in do_draw
    return self.definition(data.draw, *self.args, **self.kwargs)
tests/test_stateful_repo_ops.py:74: in v3_array_metadata
    metadata = ArrayV3Metadata(
../../miniconda3/envs/icechunk/lib/python3.12/site-packages/zarr/core/metadata/v3.py:274: in __init__
    fill_value_parsed = parse_fill_value(
../../miniconda3/envs/icechunk/lib/python3.12/site-packages/zarr/core/metadata/v3.py:573: in parse_fill_value
    and np.isclose(np.imag(fill_value), np.imag(casted_value), equal_nan=True)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

a = nan, b = nan, rtol = 1e-05, atol = 1e-08, equal_nan = True

    @array_function_dispatch(_isclose_dispatcher)
    def isclose(a, b, rtol=1.e-5, atol=1.e-8, equal_nan=False):
        """
        Returns a boolean array where two arrays are element-wise equal within a
        tolerance.

        The tolerance values are positive, typically very small numbers.  The
        relative difference (`rtol` * abs(`b`)) and the absolute difference
        `atol` are added together to compare against the absolute difference
        between `a` and `b`.

        .. warning:: The default `atol` is not appropriate for comparing numbers
                     that are much smaller than one (see Notes).

        Parameters
        ----------
        a, b : array_like
            Input arrays to compare.
        rtol : float
            The relative tolerance parameter (see Notes).
        atol : float
            The absolute tolerance parameter (see Notes).
        equal_nan : bool
            Whether to compare NaN's as equal.  If True, NaN's in `a` will be
            considered equal to NaN's in `b` in the output array.

        Returns
        -------
        y : array_like
            Returns a boolean array of where `a` and `b` are equal within the
            given tolerance. If both `a` and `b` are scalars, returns a single
            boolean value.

        See Also
        --------
        allclose
        math.isclose

        Notes
        -----
        .. versionadded:: 1.7.0

        For finite values, isclose uses the following equation to test whether
        two floating point values are equivalent.

         absolute(`a` - `b`) <= (`atol` + `rtol` * absolute(`b`))

        Unlike the built-in `math.isclose`, the above equation is not symmetric
        in `a` and `b` -- it assumes `b` is the reference value -- so that
        `isclose(a, b)` might be different from `isclose(b, a)`. Furthermore,
        the default value of atol is not zero, and is used to determine what
        small values should be considered close to zero. The default value is
        appropriate for expected values of order unity: if the expected values
        are significantly smaller than one, it can result in false positives.
        `atol` should be carefully selected for the use case at hand. A zero value
        for `atol` will result in `False` if either `a` or `b` is zero.

        `isclose` is not defined for non-numeric data types.
        `bool` is considered a numeric data-type for this purpose.

        Examples
        --------
        >>> np.isclose([1e10,1e-7], [1.00001e10,1e-8])
        array([ True, False])
        >>> np.isclose([1e10,1e-8], [1.00001e10,1e-9])
        array([ True, True])
        >>> np.isclose([1e10,1e-8], [1.0001e10,1e-9])
        array([False,  True])
        >>> np.isclose([1.0, np.nan], [1.0, np.nan])
        array([ True, False])
        >>> np.isclose([1.0, np.nan], [1.0, np.nan], equal_nan=True)
        array([ True, True])
        >>> np.isclose([1e-8, 1e-7], [0.0, 0.0])
        array([ True, False])
        >>> np.isclose([1e-100, 1e-7], [0.0, 0.0], atol=0.0)
        array([False, False])
        >>> np.isclose([1e-10, 1e-10], [1e-20, 0.0])
        array([ True,  True])
        >>> np.isclose([1e-10, 1e-10], [1e-20, 0.999999e-10], atol=0.0)
        array([False,  True])
        """
        def within_tol(x, y, atol, rtol):
            with errstate(invalid='ignore'), _no_nep50_warning():
                return less_equal(abs(x-y), atol + rtol * abs(y))

        x = asanyarray(a)
        y = asanyarray(b)

        # Make sure y is an inexact type to avoid bad behavior on abs(MIN_INT).
        # This will cause casting of x later. Also, make sure to allow subclasses
        # (e.g., for numpy.ma).
        # NOTE: We explicitly allow timedelta, which used to work. This could
        #       possibly be deprecated. See also gh-18286.
        #       timedelta works if `atol` is an integer or also a timedelta.
        #       Although, the default tolerances are unlikely to be useful
        if y.dtype.kind != "m":
            dt = multiarray.result_type(y, 1.)
            y = asanyarray(y, dtype=dt)

        xfin = isfinite(x)
        yfin = isfinite(y)
        if all(xfin) and all(yfin):
            return within_tol(x, y, atol, rtol)
        else:
            finite = xfin & yfin
            cond = zeros_like(finite, subok=True)
            # Because we're using boolean indexing, x & y must be the same shape.
            # Ideally, we'd just do x, y = broadcast_arrays(x, y). It's in
            # lib.stride_tricks, though, so we can't import it here.
>           x = x * ones_like(cond)
E           RuntimeWarning: invalid value encountered in multiply
E           Falsifying example:
E           ----------
E           state = VersionControlStateMachine()
E           state.initialize(data=data(...))
E           state.teardown()

../../miniconda3/envs/icechunk/lib/python3.12/site-packages/numpy/core/numeric.py:2358: RuntimeWarning