Reconstruction od the  WaveFront
=================================


* **Running the Test**

  **The Wavefront generator need a GPU machine**
  the generation of a simulated wavefront is done with the **wfc** script. You can test it going in the *TEST* directory.
  
    * The launch in OAR is done simply ::
    
       cd yourdirectoryforwf/TEST
       WFR  your_input.txt

    * The launch on a private PC is not more difficult, just specify the card number you want to use ::

        cd yourdirectoryforwf/TEST
        WFR  your_input.txt   my_pc_name,GPU_N0

       where GPU_N0 may be 0 or 1 or something else, it depends on your PC.
    
    **ATTENTION** :

         before runnign the example given in TEST you must create the simulated file to fit.
	 To do this you must  :

            * first run the input_fzp.txt example with the wavefront simulator

            * Then you must prepare a *numpyarray.npy* data file
                    
                  doing this you can do some sort of pretreatement. The way I do it 
                  is using a PyMca_ widget, using ipython. You better be on a recent installation.
                  At ESRF try logging on the **rnice6** cluster. There the tools are quite up-to-date.
                  Dont set any environment variable, it' already OK.

                  Now we pretreat the simulated data like this ::

                        >ipython --q4thread
              
                  now you are in the ipython environment ::

                        from PyMca import MaskImageWidget
                        w=MaskImageWidget.MaskImageWidget()
                        import h5py
                        f=h5py.File("detector_image.h5")
                        data=f['map_squareamplitude'][:]
                        w.setImageData(data)
                        w.show()
                      
                  you have now a beautiful widget from PyMca 

                           * select with the mouse a mask over the ROI

                  When you have selected the ROI ::
                      
                        w=MaskImageWidget.MaskImageWidget()
                        w.setImageData(data)
                        w.show()
                        mask = w.getSelectionMask()
                        datamasked=data*mask
                        datamasked.dump("datasim.npy")

		  Your data are now in *datasim.npy*, ready for the wavefront reconstruction

     

     * READY TO LAUNCH THE RECONSTRUCTION  ::

           WFR inputwfr_sim.txt
 



* **Inspecting the Output**


  The simulation code creates several files  

            Documentation : TODO

 
**WARNING**
      The docstrings in *.py* are not ready yet. I just include some autodoc. At least one can navigate the code 


* The parameters are dealt by *ParametersR_module.py* :

  *the following documentation has been generated automatically from the docstrings found in the source code.*

  .. automodule:: ParametersR_module
     :members: Parameters
     :noindex:

* The calculation is done by *wfr.py*  module :

  *the following documentation has been generated automatically from the docstrings found in the source code.*

  .. automodule:: wfr
     :members: 
     :noindex:



.. _PyMCA: http://pymca.sourceforge.net/