%FP_FSC_PREPROCESS 
% [recon] = FP_FSC_preprocess(recon)
%
% adjust the loaded Fourier Ptycho data for FSC calculations
%
% ** recon      cell array of reconstructions
%
% returns:
% ++ recon      cell array of reconstructions
%
% see also: aligned_FSC
%

% Academic License Agreement
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% Source Code
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% Introduction 
% •	This license agreement sets forth the terms and conditions under which the PAUL SCHERRER INSTITUT (PSI), CH-5232 Villigen-PSI, Switzerland (hereafter "LICENSOR") 
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%       "Data processing was carried out using the cSAXS ptychography MATLAB package developed by the Science IT and the coherent X-ray scattering (CXS) groups, Paul 
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%
% Additionally, any publication using the package, or any translation of the code into another computing language should cite for difference map:
% P. Thibault, M. Dierolf, A. Menzel, O. Bunk, C. David, F. Pfeiffer, High-resolution scanning X-ray diffraction microscopy, Science 321, 379–382 (2008). 
%   (doi: 10.1126/science.1158573),
% for maximum likelihood:
% P. Thibault and M. Guizar-Sicairos, Maximum-likelihood refinement for coherent diffractive imaging, New J. Phys. 14, 063004 (2012). 
%   (doi: 10.1088/1367-2630/14/6/063004),
% for mixed coherent modes:
% P. Thibault and A. Menzel, Reconstructing state mixtures from diffraction measurements, Nature 494, 68–71 (2013). (doi: 10.1038/nature11806),
% and/or for multislice:
% E. H. R. Tsai, I. Usov, A. Diaz, A. Menzel, and M. Guizar-Sicairos, X-ray ptychography with extended depth of field, Opt. Express 24, 29089–29108 (2016). 
%   (doi: 10.1364/OE.24.029089).
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function [recon] = FP_FSC_preprocess(recon, recon_fn, param)
import utils.*


% import parameters
p.object{1} = recon.object;
p.plot.FP_maskdim = io.HDF.hdf5_load(recon_fn, '/reconstruction/p/plot/FP_maskdim');
p.dx_spec = io.HDF.hdf5_load(recon_fn, '/reconstruction/p/dx_spec');
p.object_size = double(io.HDF.hdf5_load(recon_fn, '/reconstruction/p/object_size'));
p.numobjs = io.HDF.hdf5_load(recon_fn, '/reconstruction/p/numobjs');
p.z_lens = io.HDF.hdf5_load(recon_fn, '/reconstruction/p/z_lens');
p.lambda = io.HDF.hdf5_load(recon_fn, '/reconstruction/p/lambda');

if ~isempty(param.crop_asize)
    p.object{1} = crop_pad(p.object{1}, param.crop_asize); 
    p.object_size = [];
    p.object_size = size(p.object{1});
end

if param.filter_FFT
    % calculate mask
    ob_mask{1} = abs(ifftshift(filt2d_pad(p.object_size, round(p.plot.FP_maskdim/p.dx_spec(1)), round(p.plot.FP_maskdim/p.dx_spec(1)-5), 'circ')));
else
    ob_mask{1} = ones(p.object_size);
end
if isempty(param.z_lens)
    param.z_lens = p.z_lens;
end
% calculate phase factor for backpropagation
k = 2*pi/p.lambda;
objpix = p.lambda*p.z_lens/(p.object_size(1)*p.dx_spec(1));
[Xp,Yp] = get_grid(p.object_size(1,:), objpix);
pre_phase_factor = exp(1i*k*((Xp).^2+(Yp).^2)/(2*param.z_lens));

% propagate back to sample plane
obnum = 1; % fix for multiple scans
ob = (ifft2(ifftshift(p.object{obnum}(:,:,1).*ob_mask{obnum})))*p.object_size(1).*ifftshift((pre_phase_factor));
ob = utils.crop_pad(ob, round(p.object_size.*param.crop_factor));

p.objpix = objpix;
recon.object = conj(ob);
recon.p = p;



end