pyvibdmc.analysis.extract_sim_info
==================================

.. py:module:: pyvibdmc.analysis.extract_sim_info


Classes
-------

.. autoapisummary::

   pyvibdmc.analysis.extract_sim_info.SimInfo


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

.. py:class:: SimInfo(h5_name)

   Object that takes in a .hdf5 file (one of the outputs of the simulation) and provides tools for analysis.

   :param h5Name: hdf5 file
   :type str


   .. py:attribute:: fname


   .. py:method:: get_wfn(wfn_fl, ret_ang=False, get_parent_wts=False)
      :staticmethod:


      Given a .hdf5 file, return wave function and descendant weights associated with that wave function.

      :param wfn_fl: A resultant .hdf5 file from a PyVibDMC simulation
      :param ret_ang: boolean indicating returning the coordinates in angtstroms. Bohr is the default.
      :return: Coordinates array in angstroms (nxmx3), descendant weights array (n).



   .. py:method:: get_wfns(time_step_list, ret_ang=False, get_parent_wts=False)

      Extract the wave function (walker set) and descendant weights given a time step number or numbers
      :param time_step_list: a list of ints that correspond to the time steps you want the wfn from given the simulation you are working with
      :type time_step_list: int or list
      :param ret_ang: boolean indicating returning the coordinates in angtstroms. Bohr is the default.
      :param get_parent_wts: Return the continuous weights associated with the walkers at the beginning of descendant weighting.



   .. py:method:: get_vref(ret_cm=False)

      Returns vref_vs_tau array



   .. py:method:: get_pop()

      Returns population array, either ensemble size or sum of weights



   .. py:method:: get_atomic_nums()

      Returns list of atoms used in the simulation (by atomic number)



   .. py:method:: get_atom_masses()

      Returns masses used in the simulation in atomic units (mass electron)



   .. py:method:: get_zpe(onwards=1000, ret_cm=False)

      onwards is an int that tells us where to start averaging (python indexing
      starts at 0)



   .. py:method:: window_avg(blocks=5, ret_cm=False)

      Splits vref into blocks, calculates zpe in each of those blocks



   .. py:method:: get_training(training_file, ret_ang=False, ret_cm=False)
      :staticmethod:


      If using deb_training_every argument, read the files with this. Returns walkers in angstr and engs in cm-1