pencil.ism_dyn.get_masks
========================

.. py:module:: pencil.ism_dyn.get_masks

.. autoapi-nested-parse::

   Derive auxilliary data and other diagnostics from var.h5 file and
   save to new h5 file

   uses:
     compute 'data' arrays of size [nz,ny,nx] as required
     store 'time' of snapshot
     compute 'masks' for example by temperature phase
     compute summary statistics 'stats'
     compute 'structure' functions as required



Functions
---------

.. autoapisummary::

   pencil.ism_dyn.get_masks.thermal_decomposition
   pencil.ism_dyn.get_masks.derive_masks


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

.. py:function:: thermal_decomposition(ss, pars, unit_key='unit_entropy', ent_cut=[2320000000.0])

   call signature:

   thermal_decomposition(ss, pars, unit='unit_entropy', ent_cut=[2.32e9,])

   :keyword ss: dataset used for masks, default 'ss', alternate e.g.'tt'
   :keyword pars: Param() object required for units rescaling
   :keyword unit_key: label of physical units in pars to apply to code values
   :keyword ent_cut: list of boundary mask values, default see thesis
                     http://hdl.handle.net/10443/1755 Figure 5.10
                     may have multiple boundaries


.. py:function:: derive_masks(sim_path, src, dst, data_key='data/ss', par=[], comm=None, overwrite=False, rank=0, size=1, nghost=3, status='a', chunksize=1000.0, quiet=True, nmin=32, ent_cuts=[2320000000.0], mask_keys=['hot'], unit_key='unit_entropy')