:py:mod:`pemtk.fit._plotters`
=============================

.. py:module:: pemtk.fit._plotters


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


Functions
~~~~~~~~~

.. autoapisummary::

   pemtk.fit._plotters.BLMfitPlot
   pemtk.fit._plotters.lmPlotFit
   pemtk.fit._plotters.BLMsetPlot
   pemtk.fit._plotters.hvSave



.. py:function:: BLMfitPlot(self, keys=None, dataType='AFBLM', Etype='t', thres=0.01, col=None, **kwargs)

   Wrap BLMplot for data + simulation results with default params.

   TODO:
   - better plotting (HV?).
   - fix legend & colour mapping.


.. py:function:: lmPlotFit(self, keys=None, dataType='AFBLM', Etype='t', thres=0.01, **kwargs)

   Wrap lmPlot for data + simulation results with default params.



.. py:function:: BLMsetPlot(self, key='fits', dataDict='AFxr', agg=True, ref=True, overlay=['l', 'm'], pType='r', thres=0.001, sel=None, xDim=None, sq=True, drop=True, unstack=True, plotDict='plots')

   Plot sets of BLM results from Xarray datasets with Holoviews.

   For plotting individual datasets with more control, see BLMfitPlot().

   TODO:
   - add Seaborn plotting options.
   - Streamline, should be able to use recursively to stack additional plots...?

   :param agg: If True, define reduced data as hv.reduce(['Fit'], np.mean, spreadfn=np.std)
               NOTE: if False, rendering can be quite slow for large datasets.
               TODO: more options here.
   :type agg: bool, default = True
   :param ref: If True, include original fitted data in plots.
               TODO: more options here.
   :type ref: bool, default = True


.. py:function:: hvSave(self, key='plots', pTypes=None, outStem=None, outPath=None, outTypes=['png', 'html'])

   Wrapper for quick plot save routine from data dict.

   If data is a HV object, set key=None to save directly
   Update: removed this, since it's not very clear or useful (missing defaults).