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fix: Accept float64 positions in the Ritter bounding sphere - #85
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The Ritter second pass is written in Cython and only accepts float32 arrays, so `bounding_sphere` with the default or `'ritter'` method raised `ValueError: Buffer dtype mismatch, expected 'float32_t' but got 'double'` for float64 positions. `encode` casts its input to float32, so this used to be unreachable from it. Under numpy 2's promotion rules (NEP 50), numpy scalars are no longer demoted to an array's dtype, so an `Ellipsoid` whose axes are numpy float64 scalars now makes `to_ecef` return float64, and `encode` fails. On numpy 1.26 the same call succeeds. Cast positions to float32 before the Ritter pass, which matches the precision it has always used. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
kylebarron
added this pull request to stack #91
October 5, 2026 21:52
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Note
This PR was written by Claude (Claude Code), not by @kylebarron.
Fixes
encodefailing under numpy 2 when theEllipsoidaxes are numpyfloat64scalars.The bug
The Ritter bounding sphere's second pass is written in Cython and only accepts
float32.encodecasts its input tofloat32, so this used to be unreachable from it. Under numpy 2's promotion rules (NEP 50), numpy scalars are no longer demoted to the array's dtype, soto_ecefreturnsfloat64for such an ellipsoid and the Ritter pass rejects it. The same call works on numpy 1.26. Callingbounding_spheredirectly withfloat64positions fails on both versions.Fix
Cast positions to
float32before the Ritter pass. That's the precision it has always used, so output is unchanged.Tests
test_bounding_sphere_float64(default andrittermethods) andtest_encode_ellipsoid_numpy_scalars. All three fail without the fix and pass with it.🤖 Written by Claude Code