Batch Processing
----------------
A batch object can iterate over any spec object.
The command below shows how to create a :class:`tshirt.pipeline.spec_pipeline.batch_spec` object to iterate over many different :class:`tshirt.pipeline.spec_pipeline.spec` methods.
Here is an example on how to run :any:`spec_pipeline.spec.plot_wavebin_series` over the batch object.

.. code-block:: python

   bspec = spec_pipeline.batch_spec(batchFile='corot1_batch_file.yaml')
   bspec.batch_run('plot_wavebin_series', nbins=1, interactive=True) 
   
This could be done on any method that spec can.
One way to check if the batch file is working and test a method is to have the batch object spit out a :class:`tshirt.pipeline.spec_pipeline.spec` object using :any:`spec_pipeline.batch_spec.return_spec_obj`.

.. code-block:: python

   bspec = spec_pipeline.batch_spec(batchFile='corot1_batch_file.yaml')
   spec = bspec.return_spec_obj()
   spec.plot_one_spec()
   
Bokeh Interactive Plotting
--------------------------

How-To Use Interactive plots
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
Note that when running ``tshirt`` in a Jupyter notebook setting, use ``output_notebook`` to generate embedded interactive plots within the Jupyter notebook space.

.. code-block:: python

   from bokeh.io import output_notebook
   output_notebook()
   spec = spec_pipeline.spec()
   spec.do_extraction()
   spec.plot_wavebin_series(interactive=True)


More information on Interactive Plotting
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
Bokeh is an interactive visualization library that can easily make interactive plots, dashboards, and data applications. Before attempting to create an interactive plot follow the instructions on how to install `Bokeh`_ .

.. _Bokeh: https://docs.bokeh.org/en/latest/docs/user_guide/quickstart.html 

The Bokeh interface has a variety of modules. In the case of creating an interactive plot with tshirt’s ``spec_pipeline`` module, import specific functions of the ``bokeh.io`` module, and the ``bokeh.plotting`` module. From the ``bokeh.plotting`` module import ``figure`` to create a new figure for plotting if needed. From ``bokeh.io`` import the following:

* ``output_notebook`` to configure the default output state and generate the output in the notebook cells. 
* ``show`` to immediately display a Bokeh object or application.
* ``push_notebook`` to update Bokeh plots in a Jupyter notebook output cells with new data or property values.


The code below shows an example of how to import these various functions.

.. code-block:: python

   from bokeh.io import push_notebook, show, output_notebook
   from bokeh.plotting import figure
   output_notebook()