MFE_calculator
==============

.. py:module:: MFE_calculator


Attributes
----------

.. autoapisummary::

   MFE_calculator._PAIRS


Classes
-------

.. autoapisummary::

   MFE_calculator.RNAFolder
   MFE_calculator.RNAFolderBase
   MFE_calculator.RNAFolderBase2
   MFE_calculator.RNASolution
   MFE_calculator.RNASolutionBase
   MFE_calculator.RNASolutionBase2


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

.. py:class:: RNAFolder(loop_min=0, energies=None)

   Bases: :py:obj:`RNAFolderBase2`


   An RNA folding algorithm and parameters

   An instance holds all the configuration necessary to
   solve an RNA folding problem. Note that energies are
   the free-energy (a more negative value for the more
   favourable pairings).


   .. py:method:: solve(rna)


.. py:class:: RNAFolderBase(loop_min=0, energies=None)

   An RNA folding algorithm and parameters

   An instance holds all the configuration necessary to
   solve an RNA folding problem. Note that energies are
   the free-energy (a more negative value for the more
   favourable pairings).


   .. py:attribute:: MAX_BULGE
      :value: 20



   .. py:attribute:: MAX_HAIRPIN
      :value: 20



   .. py:attribute:: MAX_INTERNAL
      :value: 20



   .. py:method:: _helix_lookups(energies)
      :staticmethod:


      Create look-up tables for free energy in helices



   .. py:method:: _interpolated_table(energies, size, key, fmt = '02d')
      :staticmethod:


      Read values key01, key02, ... to array interpolating missing values.

      We use this to encode e.g. the hairpin loop energies in a table
      we can use incrementally during minimisation.



   .. py:method:: _loop_lookups(energies)
      :staticmethod:


      Create look-up tables for loop free energy in loops



   .. py:method:: _special_lookups(energies, dflt=None)
      :staticmethod:


      Get misc special free energy parameters



   .. py:attribute:: lmin
      :value: 0



   .. py:attribute:: non_pairing
      :value: None



   .. py:method:: print_hairpin_fe(n)


   .. py:method:: print_stack_fe(rp, sp)


   .. py:method:: print_term_fe(rp, an, bn)


.. py:class:: RNAFolderBase2(loop_min=0, energies=None)

   Bases: :py:obj:`RNAFolderBase`


   An RNA folding algorithm and parameters

   An instance holds all the configuration necessary to
   solve an RNA folding problem. Note that energies are
   the free-energy (a more negative value for the more
   favourable pairings).


   .. py:method:: closed_energy(soln, i, j)

      Minimum energy and mode of [i, j] closed by pairing (i,j).

      If the pair is forbidden (not AU, CG, GC, GU, UA or UG) the method
      returns the self.non_pairing energy (normally math.inf), and the
      returned mode is -1. Otherwise, the method compares the minimum energy
      obtained by pairing (i,j) across [i+1, j-1] considered as open and
      closed, and returns the lower energy and mode (0=open, 1=closed).



   .. py:method:: open_energy(soln, i, j)

      Minimum energy of [i, j] without pairing (i,j).

      The method seeks a lowest energy for [i,j], considering j unpaired
      or paired with any interior nucleotide k, where i<k<j.



.. py:class:: RNASolution(rna)

   Bases: :py:obj:`RNASolutionBase2`


   An RNA folding solution and working data

   An instance holds the working data used when solving
   an RNA folding problem, and afterwards to generate.
   various expressions of the solution.


   .. py:method:: as_dots()

      Dot-bracket form of the fold



   .. py:method:: walk_range(i, j)

      Walk the range [i,j] inclusive using min(U,V).

      We use this when backtracking the energy calculation to discover
      the lowest energy structure, in contexts where we know the subsequent
      energy calculation will have chosen the lesser of the closed (j pairs
      with i) and open (j pairs with something else or is unpaired) energy.



   .. py:method:: walk_range_ex(i, j, closed)

      Walk the range [i,j] inclusive specifying open or closed.

      We use this when backtracking the energy calculation to discover
      the lowest energy structure. Nodes (the data for a range) in our
      algorithm offer both closed (j pairs with a) and open (j pairs
      with something else or is unpaired) energy, and a subsequent
      nodes choose between them in offering their own energies. When
      backtracking, determining the structure of [i,j] in the minimum
      energy configuration may be informed by knowledge of that choice,
      provided through the 'closed' argument.



.. py:class:: RNASolutionBase(rna)

   An RNA folding solution and working data

   An instance holds the working data used when solving
   an RNA folding problem, and afterwards to generate.
   various expressions of the solution.


   .. py:attribute:: K


   .. py:attribute:: M


   .. py:attribute:: U


   .. py:attribute:: V


   .. py:method:: energy()

      The free energy of the minimum energy solution



   .. py:method:: getK(i, j)


   .. py:method:: getM(i, j)


   .. py:method:: getU(i, j)


   .. py:method:: getV(i, j)


   .. py:attribute:: irna


.. py:class:: RNASolutionBase2(rna)

   Bases: :py:obj:`RNASolutionBase`


   An RNA folding solution and working data

   An instance holds the working data used when solving
   an RNA folding problem, and afterwards to generate.
   various expressions of the solution.


   .. py:method:: branches(i, j)

      Enumerate the branches in the open interval [i,j].

      When we consider the energy freed by potential pair (i-1,j+1),
      we must understand what open structure it "closes". It is enough
      to list the branches (helices) chosen when forming the open
      conformation of [i,j], each identified by its initial pair, in
      ascending order of first member.

      The number of branches distingishes 0: hairpin, 1: internal or bulge
      loop, and >1: multiloop, while in case 1 the differences between the
      ends of the proposed closing and those of the single base pair
      distinguish amongst bulges, interior and muylti-branch loops.
      A single branch does not signify helix continuation, since that is
      a closed structure.



   .. py:method:: get_arrays()

      Get references to the K, U and V arrays



.. py:data:: _PAIRS
   :value: ('AU', 'CG', 'GC', 'GU', 'UA', 'UG')