feat: schema validation, ipsatize unification, and CircEResults container#132
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MitchellAcoustics wants to merge 9 commits intodevfrom
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feat: schema validation, ipsatize unification, and CircEResults container#132MitchellAcoustics wants to merge 9 commits intodevfrom
MitchellAcoustics wants to merge 9 commits intodevfrom
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…iner Implements the top-priority recommendations from the SATP circumplex validation analysis review: - fix: SATPSchema now raises SchemaErrors by default instead of silently dropping invalid rows (drop_invalid_rows=False); fit_circe gains an errors='raise'|'warn' parameter for opt-in lenient behaviour - fix: fit_circe uses grand-mean centering (1 scalar/participant) matching the published SATP R analysis; column-wise centering (8 scalars/participant) was the previous incorrect default, causing SRMR values ~0.005 higher than canonical R values - feat: add soundscapy.surveys.ipsatize(method='grand_mean'|'column_wise'| 'row_wise') — unified ipsatization entry point living in core surveys/ module (no R dependency); person_center() becomes a thin wrapper with a deprecation note - feat: fit_circe returns CircEResults instead of a bare DataFrame; provides .table (DataFrame), .for_model(CircModelE), ._repr_html_(), and len(); CircE dataclass instances are preserved with all typed attributes - test: new TestIpsatize in test/surveys/ (core, no R); new CircEResults tests; existing test_circe.py updated for new return type Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- fix(ipsatize): use np.nanmean() for grand-mean centering so participants with partial NaN data get a valid grand mean from available values, rather than the whole participant being silently wiped when any NaN is present - fix(fit_circe): use .loc[~index.isin()] instead of .drop(index=) in the errors='warn' path to correctly handle duplicate DataFrame indices; report accurate remaining row count; wrap second validate() call to prevent unhandled SchemaErrors leaking from the warn path - docs: clarify models=[] returns CircEResults not a DataFrame; disambiguate 'the default' in person_center deprecation note Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
The test introduces NaN values to verify listwise deletion, but with drop_invalid_rows=False (the new default), NaN PAQ values fail schema validation before the assertion is reached. Passing errors="warn" keeps the test focused on its intent (listwise deletion) rather than schema validation. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
v0.24.2 had a bug handling dotted keys in inline tables that surfaced under Python 3.14 in CI, causing toml-sort-fix to modify pyproject.toml on every run. v0.24.3 fixes this. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Causes spurious CI failures under Python 3.14 — modifies pyproject.toml on every run despite the file already being correctly sorted. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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Summary
SATPSchemasilent drop — changeddrop_invalid_rows = Falseso invalid rows raise aSchemaErrorsexception rather than being silently discarded; addederrors: Literal["raise", "warn"]parameter tofit_circefollowing pandas conventionipsatize()—fit_circenow uses grand-mean centering (one scalar per participant, matching the published R analysis) instead of the previous column-wise centering;ipsatize(method=...)added tosurveys.processingwith"grand_mean"(default),"column_wise", and"row_wise"methods;person_center()becomes a thin wrapper with a deprecation noteCircEResultscontainer —fit_circenow returns a typedCircEResultsdataclass (.table,.for_model(),.__len__(),._repr_html_()) instead of a barepd.DataFrame; exported fromsoundscapy.satpand lazily fromsoundscapyTest plan
uv run pytest test/satp/ -m optional_deps— CircE integration tests (requires R + CircE)uv run pytest test/surveys/test_survey_processing.py::TestIpsatize— new ipsatize unit tests (no R required)uv run pytest --xdoctest src/soundscapy/satp/circe.py— doctestsquarto render docs/tutorials/SATP_CircE_Analysis.qmd— verified locally, all 16 languages complete, df values match canonical exactly🤖 Generated with Claude Code