straindesign.speedy_fva
=======================

.. py:module:: straindesign.speedy_fva

.. autoapi-nested-parse::

   Accelerated FVA using scan LPs and bound scanning.

   Standard FVA solves 2*n independent LPs (max and min for each reaction).
   This implementation reduces LP count via a two-phase approach:

   Phase 1 — Scan LPs (cheap, resolve ~50-70% of bounds):
     a. v=0 feasibility: free resolutions when zero flux is feasible
     b. min(sum(|x|)): pushes reactions toward zero, resolves lb=0/ub=0 bounds
     c. Push-to-bounds: directed objectives push unresolved reactions toward
        their variable bounds, with dual simplex warm-start for fast re-solves
     Each scan LP solution is processed by bound scanning (vectorized at-bound
     check that marks reactions whose flux equals their variable bound).

   Phase 2 — Individual LPs for remaining unresolved objectives:
     Sequential (warm-started) or parallel (SDPool) dispatch depending on
     problem size and thread count.  Sequential mode includes co-optimization
     scanning: each LP vertex is checked for other reactions at their bounds.





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

.. py:function:: speedy_fva(model, **kwargs)

   Accelerated FVA using global scan LPs and KKT-based optimality propagation.

   Returns the same DataFrame as straindesign.lptools.fva.

   :param model:
   :type model: cobra.Model
   :param solver:
   :type solver: str, optional
   :param constraints:
   :type constraints: str or list, optional
   :param compress: Compress the model (coupled compression + conservation removal) before
                    running FVA, then expand results back.  None = auto (True if n >= 200).
   :type compress: bool or None, optional (default None)
   :param precheck: Run global scan LPs (min/max sum(|x|)) in Phase 1 to pre-resolve many
                    objectives without individual LPs.  None = auto (always True).
   :type precheck: bool or None, optional (default None)
   :param threads: Number of parallel workers for Phase 2 dispatch.  None = auto
                   (Configuration().processes if n >= 1000, else 1).
   :type threads: int or None, optional (default None)
   :param verbose:
   :type verbose: bool, optional (default False)

   :rtype: pandas.DataFrame with columns 'minimum' and 'maximum', indexed by reaction ID.