Add RescaleDiagnostics to return detailed rescaling information - #119
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feat(ellcloud): add RescaleDiagnostics and return_diagnostics to rescale() (#105) - Upgrade codecov/codecov-action from v4.0.1 to v5; add continue-on-error: true so a Codecov network glitch cannot fail an otherwise-passing CI run. - Add frozen dataclass RescaleDiagnostics (scale, pre_summary, post_summary) exported from ellphi and ellcloud. - rescale() gains an opt-in return_diagnostics=False flag; default path is fully backward-compatible. - Update ellcloud.pyi with @overload stubs for both call signatures. - Add three new regression tests covering type, shape, pre/post relationship, and consistency with the default return path. https://claude.ai/code/session_01S8zuHdfhWRruSejHtQZo6L
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Addresses Codex review: a non-literal bool variable passed as return_diagnostics was rejected by type checkers. Add a third overload accepting bool -> float | RescaleDiagnostics as the fallback case. https://claude.ai/code/session_01S8zuHdfhWRruSejHtQZo6L
This was referenced Jul 3, 2026
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Summary
This PR adds a new
RescaleDiagnosticsdataclass that provides detailed information about the rescaling operation performed byEllipseCloud.rescale(). Users can now optionally retrieve pre- and post-rescaling summaries along with the scale factor.Key Changes
New
RescaleDiagnosticsdataclass: A frozen dataclass containing:scale: The scaling factor appliedpre_summary: Per-axis aggregate semi-axis lengths before rescalingpost_summary: Per-axis aggregate semi-axis lengths after rescalingEnhanced
EllipseCloud.rescale()method:return_diagnosticsparameter (defaultFalsefor backward compatibility)floatwhenreturn_diagnostics=False(existing behavior)RescaleDiagnosticswhenreturn_diagnostics=TrueType hints: Added overloaded type signatures in
.pyistub file to properly reflect the conditional return type based on thereturn_diagnosticsparameterPublic API: Exported
RescaleDiagnosticsfrom main__init__.pyand.pyifilesTests: Added three comprehensive test cases:
RescaleDiagnosticstype and shape of returned datapost_summary = pre_summary / scaleImplementation Details
The diagnostics are computed from the existing
ell_scalesarray that was already being calculated internally, so there is minimal performance overhead. The implementation maintains full backward compatibility by defaultingreturn_diagnosticstoFalse.https://claude.ai/code/session_01S8zuHdfhWRruSejHtQZo6L