src.dackar.RCA.orchestrators.ishikawa_evaluator
===============================================

.. py:module:: src.dackar.RCA.orchestrators.ishikawa_evaluator

.. autoapi-nested-parse::

   ishikawa_evaluator — Deterministic Ishikawa (fishbone) matrix builder.

   Extracted from rca_reasoning_orchestrator.py.  The parent module re-exports
   HeuristicIshikawaEvaluatorV1 for backward-compatible imports.



Attributes
----------

.. autoapisummary::

   src.dackar.RCA.orchestrators.ishikawa_evaluator.JsonDict


Classes
-------

.. autoapisummary::

   src.dackar.RCA.orchestrators.ishikawa_evaluator.HeuristicIshikawaEvaluatorV1


Functions
---------

.. autoapisummary::

   src.dackar.RCA.orchestrators.ishikawa_evaluator.utcnow_iso


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

.. py:data:: JsonDict

.. py:function:: utcnow_iso()

.. py:class:: HeuristicIshikawaEvaluatorV1

   First deterministic Ishikawa evaluator.

   Builds a structured fishbone-style matrix from:
     - candidate hypotheses
     - KG context
     - temporal support
     - retrieved evidence
     - optional PM / operational context


   .. py:attribute:: CATEGORY_ORDER
      :value: ['equipment_hardware', 'process_procedure', 'measurement_instrumentation',...



   .. py:method:: evaluate(event, telemetry_summary, kg_context, tskr_patterns, causality_candidates, evidence_bundle, operational_context, pm_compliance, run_context)

      Build the Ishikawa contributing-factor matrix for an event.

      Assembles category-grouped rows from the causal candidates (each cited
      with its *own* supporting evidence — see
      :meth:`_supporting_evidence_by_candidate`), telemetry/TSKR measurement
      signals, maintenance and operating-context factors, process evidence,
      and KG-context factors.

      :param event: Target event (must carry ``event_id`` or ``id``), its telemetry
                    summary, and the KG neighbourhood.
      :param telemetry_summary: Target event (must carry ``event_id`` or ``id``), its telemetry
                                summary, and the KG neighbourhood.
      :param kg_context: Target event (must carry ``event_id`` or ``id``), its telemetry
                         summary, and the KG neighbourhood.
      :param tskr_patterns: TSKR chain-position patterns, or None.
      :param causality_candidates: Ranked candidate hypotheses and their retrieved evidence.
      :param evidence_bundle: Ranked candidate hypotheses and their retrieved evidence.
      :param operational_context: Optional supporting artifacts, or None.
      :param pm_compliance: Optional supporting artifacts, or None.
      :param run_context: Orchestrator run context (``run_id``).

      :returns: An Ishikawa matrix conforming to ``schemas/ishikawa_matrix.json``
                (categories, rows, and a summary of top candidates).
      :rtype: JsonDict



   .. py:method:: _candidate_rows(causality_candidates, evidence_bundle)


   .. py:method:: _supporting_evidence_by_candidate(evidence_bundle)

      Index the evidence bundle by the candidate each hit supports.

      Groups the bundle's ``results`` by their ``metadata.linked_candidate_id``
      (falling back to ``metadata.candidate_id``), keeping only non-superseded,
      ``support_role == "supporting"`` hits, so that each Ishikawa row cites the
      evidence retrieved for *its own* candidate rather than the first three
      snippet ids in the bundle.

      :param evidence_bundle: Evidence bundle whose ``results`` list holds normalized retrieval
                              hits (top-level ``snippet_id`` / ``support_score`` / ``superseded``,
                              with ``support_role`` and candidate linkage under ``metadata``).
      :type evidence_bundle: JsonDict

      :returns: Maps ``candidate_id`` to its supporting snippet ids, highest
                ``support_score`` first and capped at three. Candidates with no
                supporting evidence are absent (callers default to ``[]``).
      :rtype: Dict[str, List[str]]



   .. py:method:: _measurement_rows(telemetry_summary, tskr_patterns)


   .. py:method:: _maintenance_rows(pm_compliance, causality_candidates)


   .. py:method:: _operating_context_rows(operational_context, event)


   .. py:method:: _process_rows(evidence_bundle)


   .. py:method:: _kg_context_rows(kg_context)


   .. py:method:: _group_rows(rows)