Fix JAX array leak from PointSolver into Grid2DIrregular#410
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When the solver uses a JAX backend, the final boolean-indexed solution was a JAX DeviceArray. Wrapping it in Grid2DIrregular without conversion caused downstream np.array() calls in the visualizer to raise: ValueError: object __array__ method not producing an array Fix: convert solution to numpy via np.asarray() before constructing the return Grid2DIrregular. Safe because solve() is never called inside jax.jit (variable-length boolean indexing prevents it). Also updates the Returns docstring to document the numpy-backed guarantee. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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Summary
PointSolver.solve()runs with a JAX backend, the boolean-indexedsolutionis a JAXDeviceArray. Wrapping it directly inaa.Grid2DIrregularproduced a JAX-backed object that propagated throughresult.pyintoPositionsLH.positionsand eventually into the visualizer.plotter.pycallsnp.array(positions.array)which raisedValueError: object __array__ method not producing an arrayon certain JAX versions.np.asarray()before the finalGrid2DIrregularconstruction inPointSolver.solve(). This is safe —solve()is never called insidejax.jit(variable-length boolean indexing prevents it), and all downstream consumers expect numpy-backed coordinates.Returnsdocstring to document the numpy-backed guarantee.Test plan
python -m pytest test_autolens/)np.asarray()on a numpy array is a zero-copy no-op — no regression on the numpy path🤖 Generated with Claude Code