.. _imaginary:

=====================================
Adding the Imaginary Refractive Index
=====================================

In contrast to RasCAL1, RAT allows the inclusion of the imaginary part of the refractive index to the project. The exact method of doing this varies according to the calculation type,
but at the project top-level, the method of enabling it is always the same. If the project is called 'problem', then:

.. tab-set-code::
    .. code-block:: Matlab

        problem.absorption = true;

    .. code-block:: Python

        problem.absorption = True

How this is then handled depends on the calculation type.

**********************
Standard Layers Models
**********************
The imaginary refractive index appears as a new column in the 'Layers' block.

.. tab-set::
    :class: tab-label-hidden
    :sync-group: code

    .. tab-item:: Matlab
        :sync: Matlab

        .. output:: Matlab

          problem = load('source/tutorial/data/monolayerExample.mat');
          problem = problem.problem;
          problem.absorption = true;
          problem.layers.displayTable()

    .. tab-item:: Python 
        :sync: Python
        
        .. output:: Python

            # replace with a better project reading method when we have one...
            with open('source/tutorial/data/monolayer_example.py', "r") as f:
                script = f.read()
            locals = {}
            exec(script, None, locals)
            problem = locals['problem']
            problem.absorption = True
            print(problem.layers)

Then, the value of this column are set (from the Parameters block) in the same way as all the other cells in the table.

*************
Custom Models
*************
For custom models, an extra column is also required in the output from the custom function.

So, for example, in the */examples/miscellaneous/absorption* folder, there is a Custom Layers example including absorption. In this example (a bilayer on a gold surface)
an imaginary SLD is required for the metal layers:

.. tab-set-code::
    .. code-block:: Matlab

        GOLD = [goldThick goldSLD goldISLD goldRough];
        alloyUp = [alloyThick alloySLDUp alloyISLDUp alloyRough];
        alloyDown = [alloyThick alloySLDDown alloyISLDDown alloyRough];
    
    .. code-block:: Python

        gold = [goldThick, goldSLD, goldISLD, goldRough]
        alloyUp = [alloyThick, alloySLDUp, alloyISLDUp, alloyRough]
        alloyDown = [alloyThick, alloySLDDown, alloyISLDDown, alloyRough]


but there is no imaginary component expected for the organic layers (but the extra column is still necessary).

.. tab-set-code::
    .. code-block:: Matlab

        BILTAILS = [thickTail, sldTail, 0, bilayerRough]
        BILHEAD = [thickHead, sldHead, 0, bilayerRough]
        BILME = [thickMe, sldMe, 0, bilayerRough]

    .. code-block:: Python
        
        BILTAILS = [thickTail, sldTail, 0, bilayerRough]
        BILHEAD = [thickHead, sldHead, 0, bilayerRough]
        BILME = [thickMe, sldMe, 0, bilayerRough]

For custom XY models, it is necessary to construct a profile which represents the imaginary SLD across the sample, and this then appears as am extra column in the output:

.. code-block:: console

    output = [X1,    SLD1,    SLD_im_1,
              X2,    SLD2,    SLD_im_2,
                    ...
              Xn,    SLDn,    SLD_im_n] ;