[BUG] Fix zero-distance instability in Hidalgo (#3068)

[satwiksps]

[BUG] Fix zero-distance instability in Hidalgo (#3068)

• Fixes [BUG][Hidalgo] AssertionError: assert rmax > 0 #3068.

What does this implement/fix? Explain your changes.

This PR resolves a numerical instability in the Hidalgo segmenter that occurs when two or more rows in the input data are identical or extremely close. In such cases, the nearest-neighbor search returns r1 = 0 for some points, and the original implementation computed mu = r2 / r1. This produced infinite values for mu, which then propagated into downstream parameters (such as b1), eventually causing a crash in the Gibbs sampler (sample_d) due to invalid likelihood calculations.

To fix this, a small numerical epsilon (1e-12) is introduced when computing mu, ensuring that the denominator is never zero. This preserves normal behavior for valid datasets, while preventing the zero-division crash that triggered the issue. This approach follows @TonyBagnall's guidance from the issue discussion. A local regression test confirms that the real dataset from issue #3068 now runs without errors.

Does your contribution introduce a new dependency?

No new dependencies.

Any other comments?

• The fix is deliberately minimal and targeted at the exact origin of the failure.
• Normal datasets behave exactly as before.
• Closes [BUG][Hidalgo] AssertionError: assert rmax > 0 #3068

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