coco_pipe.report.variance
=========================

.. py:module:: coco_pipe.report.variance

.. autoapi-nested-parse::

   Reusable scientific report section for subject-alignment diagnostics.



Functions
---------

.. autoapisummary::

   coco_pipe.report.variance.validate_subject_alignment_diagnostics
   coco_pipe.report.variance.select_subject_alignment_diagnostics
   coco_pipe.report.variance.build_alignment_coverage_section
   coco_pipe.report.variance.build_alignment_tradeoff_section
   coco_pipe.report.variance.build_subject_alignment_diagnostics_section


Module Contents
---------------

.. py:function:: validate_subject_alignment_diagnostics(diagnostics)

   Validate and copy the generic subject-alignment diagnostics table.


.. py:function:: select_subject_alignment_diagnostics(diagnostics, *, cohort_name, population)

   Validate and select one exact cohort/population diagnostic assessment.


.. py:function:: build_alignment_coverage_section(diagnostics, *, title = 'Cross-Model Diagnostic Coverage')

   Compare exact diagnostic populations across embedding models.


.. py:function:: build_alignment_tradeoff_section(performance, diagnostics, *, title = 'Performance-Alignment Trade-off')

   Join paired decoding and leakage deltas and mark Pareto-optimal transforms.


.. py:function:: build_subject_alignment_diagnostics_section(diagnostics, *, scatter_figure = None, title = 'Subject Alignment Diagnostics')

   Build a scientific before/after report section for subject alignment.

   The section tests the intended trade-off: subject-identifiable structure
   should decrease while label-relevant structure is retained.  It supports
   the tidy output of :func:`coco_pipe.diagnostics.variance_decomposition_report`.
   The optional scatter is caller-provided because embedding loading and
   projection are dataset-specific and are qualitative only.