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%LOAD_DATA prepare filenames and load data
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% Academic License Agreement
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%
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% Source Code
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%
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% Introduction
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% • 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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% will grant you (hereafter "LICENSEE") a royalty-free, non-exclusive license for academic, non-commercial purposes only (hereafter "LICENSE") to use the cSAXS
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% ptychography MATLAB package computer software program and associated documentation furnished hereunder (hereafter "PROGRAM").
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%
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% Terms and Conditions of the LICENSE
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% 1. LICENSOR grants to LICENSEE a royalty-free, non-exclusive license to use the PROGRAM for academic, non-commercial purposes, upon the terms and conditions
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% hereinafter set out and until termination of this license as set forth below.
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% 2. LICENSEE acknowledges that the PROGRAM is a research tool still in the development stage. The PROGRAM is provided without any related services, improvements
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% or warranties from LICENSOR and that the LICENSE is entered into in order to enable others to utilize the PROGRAM in their academic activities. It is the
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% LICENSEE’s responsibility to ensure its proper use and the correctness of the results.”
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% 3. THE PROGRAM IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR
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% A PARTICULAR PURPOSE AND NONINFRINGEMENT OF ANY PATENTS, COPYRIGHTS, TRADEMARKS OR OTHER RIGHTS. IN NO EVENT SHALL THE LICENSOR, THE AUTHORS OR THE COPYRIGHT
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% HOLDERS BE LIABLE FOR ANY CLAIM, DIRECT, INDIRECT OR CONSEQUENTIAL DAMAGES OR OTHER LIABILITY ARISING FROM, OUT OF OR IN CONNECTION WITH THE PROGRAM OR THE USE
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% OF THE PROGRAM OR OTHER DEALINGS IN THE PROGRAM.
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% 4. LICENSEE agrees that it will use the PROGRAM and any modifications, improvements, or derivatives of PROGRAM that LICENSEE may create (collectively,
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% "IMPROVEMENTS") solely for academic, non-commercial purposes and that any copy of PROGRAM or derivatives thereof shall be distributed only under the same
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% license as PROGRAM. The terms "academic, non-commercial", as used in this Agreement, mean academic or other scholarly research which (a) is not undertaken for
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% profit, or (b) is not intended to produce works, services, or data for commercial use, or (c) is neither conducted, nor funded, by a person or an entity engaged
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% in the commercial use, application or exploitation of works similar to the PROGRAM.
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% 5. LICENSEE agrees that it shall make the following acknowledgement in any publication resulting from the use of the PROGRAM or any translation of the code into
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% another computing language:
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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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% Scherrer Institut, Switzerland."
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%
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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:
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% P. Thibault, M. Dierolf, A. Menzel, O. Bunk, C. David, F. Pfeiffer, High-resolution scanning X-ray diffraction microscopy, Science 321, 379–382 (2008).
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% (doi: 10.1126/science.1158573),
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% for maximum likelihood:
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% P. Thibault and M. Guizar-Sicairos, Maximum-likelihood refinement for coherent diffractive imaging, New J. Phys. 14, 063004 (2012).
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% (doi: 10.1088/1367-2630/14/6/063004),
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% for mixed coherent modes:
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% P. Thibault and A. Menzel, Reconstructing state mixtures from diffraction measurements, Nature 494, 68–71 (2013). (doi: 10.1038/nature11806),
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% and/or for multislice:
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% 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).
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% (doi: 10.1364/OE.24.029089).
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% 6. Except for the above-mentioned acknowledgment, LICENSEE shall not use the PROGRAM title or the names or logos of LICENSOR, nor any adaptation thereof, nor the
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% names of any of its employees or laboratories, in any advertising, promotional or sales material without prior written consent obtained from LICENSOR in each case.
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% 7. Ownership of all rights, including copyright in the PROGRAM and in any material associated therewith, shall at all times remain with LICENSOR, and LICENSEE
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% agrees to preserve same. LICENSEE agrees not to use any portion of the PROGRAM or of any IMPROVEMENTS in any machine-readable form outside the PROGRAM, nor to
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% make any copies except for its internal use, without prior written consent of LICENSOR. LICENSEE agrees to place the following copyright notice on any such copies:
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% © All rights reserved. PAUL SCHERRER INSTITUT, Switzerland, Laboratory for Macromolecules and Bioimaging, 2017.
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% 8. The LICENSE shall not be construed to confer any rights upon LICENSEE by implication or otherwise except as specifically set forth herein.
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% 9. DISCLAIMER: LICENSEE shall be aware that Phase Focus Limited of Sheffield, UK has an international portfolio of patents and pending applications which relate
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% to ptychography and that the PROGRAM may be capable of being used in circumstances which may fall within the claims of one or more of the Phase Focus patents,
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% in particular of patent with international application number PCT/GB2005/001464. The LICENSOR explicitly declares not to indemnify the users of the software
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% in case Phase Focus or any other third party will open a legal action against the LICENSEE due to the use of the program.
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% 10. This Agreement shall be governed by the material laws of Switzerland and any dispute arising out of this Agreement or use of the PROGRAM shall be brought before
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% the courts of Zürich, Switzerland.
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function [ p ] = load_data( p )
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import math.*
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import utils.*
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detStorage = p.detectors(p.scanID).detStorage;
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%% VIRTUAL LOADING FUNCTION THAT GENERATES ARTIFICIAL DATA
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%% adjust positions , apply affine corrections from template and distorsion from p.simulation.affine_matrix
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if isempty(p.affine_matrix)
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p.affine_matrix = [1,0;0,1];
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end
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if ~isfield(p.simulation, 'affine_matrix') || isempty(p.simulation.affine_matrix)
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p.simulation.affine_matrix = [1,0;0,1];
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end
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%% calculate the positions
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positions_0 = p.positions; % store the p.positions and return the values at the end of this function
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tmp = p;
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tmp.affine_matrix = -p.simulation.affine_matrix * inv(p.affine_matrix); % first remove the already applied affine matrix and then apply affine matrix from simulation
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for ii = 1:p.numscans
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% add there a small random global offset for the positions
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rng(p.scan_number(ii)) % reset randomization to guarantee repeatability
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offset = 0.3; % times average step
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avg_step = sqrt(prod(max(tmp.positions_real(p.scanidxs{ii},:)) - min(tmp.positions_real(p.scanidxs{ii},:))) / p.numpts(ii));
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tmp.positions_real(p.scanidxs{ii},:) = tmp.positions_real(p.scanidxs{ii},:) + randn(1,2) * avg_step * offset;
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end
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% standard farfield ptychography
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if check_option(p.simulation, 'z') && strcmpi(p.prop_regime, 'farfield')
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tmp.dx_spec = tmp.lambda*tmp.simulation.z ./ (p.asize*p.ds); % resolution in the specimen plane
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tmp.dx_spec = tmp.dx_spec ./ cosd(tmp.sample_rotation_angles(1:2)); % account for a tilted sample ptychography
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end
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tmp.share_object_ID = ones(p.numscans,1);
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tmp = core.ptycho_adjust_positions( tmp );
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if p.simulation.position_uncertainty > 0
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tmp.positions = tmp.positions + randn(sum(p.numpts),2)*p.simulation.position_uncertainty*mean(p.dx_spec);
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utils.verbose(3, 'Included position errors, std=%3.2gnm , %3.2gpx', p.simulation.position_uncertainty*1e9, p.simulation.position_uncertainty / mean(p.dx_spec) );
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end
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% Extra offset of positions given in simulation -> subtract padding
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% provided in p structure and instead add padding from simulation structure
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p.simulation.positions = tmp.positions;
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p.simulation.positions_real = tmp.positions_real;
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%% create object
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if ~check_option(p.simulation, 'positions_pad')
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p.simulation.positions_pad = [0,0];
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end
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% Compute object sizes
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if p.share_object
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p.object_size = ceil(p.asize + max(p.simulation.positions) + p.positions_pad+ p.simulation.positions_pad(1,:));
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else
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for ii = 1:p.numscans
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p.object_size(ii,:) = ceil(p.asize + max(p.simulation.positions(p.scanidxs{ii},:)) + p.positions_pad + p.simulation.positions_pad(min(end,ii),:));
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end
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end
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% Generate object using parameters from artificial data template
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[p.simulation.obj, p.simulation.ref_index] = detector.virtual.create_object(p);
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if get_option(p, 'fourier_ptycho')
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warning('FIXME')
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keyboard
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p = fourier_ptycho_data(p);
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end
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p.simulation.probe = p.probes;
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if ~p.simulation.apply_sub_px_shifts
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p.positions = round(p.positions);
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p.simulation.positions = round(p.simulation.positions);
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end
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p.positions = p.simulation.positions;
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if p.simulation.sample_rotation_angles
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% modify the scanning positions to account for the tilted sample geometry
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p.positions = p.positions .* cosd(p.simulation.sample_rotation_angles([1,2]));
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end
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sub_px_shift = p.positions-round(p.positions);
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if any(p.simulation.sample_rotation_angles)
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% get propagators to the tilted plane or plane rotated around beam axis
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[fwd_propag_fun, back_propag_fun] = get_tilted_plane_propagators(p.probes, p.simulation.sample_rotation_angles,...
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p.lambda, p.dx_spec);
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end
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%% calculate views
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Nlayers = size(p.simulation.obj{p.scanID},4);
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if p.share_object
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obnum = 1;
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else
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obnum = p.scanID;
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end
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verbose(0, 'Creating artificial dataset')
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% auxiliar windows for subpixel shifting
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win = 0.1+0.9*tukeywin(p.asize(1),0.05) .* tukeywin(p.asize(2), 0.05)';
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iter = zeros([p.asize, length(p.scanidxs{obnum}), p.probe_modes*p.object_modes], 'like', p.simulation.obj{p.scanID});
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for prmode = 1:p.probe_modes
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for obmode = 1:p.object_modes
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p.simulation.obj{obnum} = single(p.simulation.obj{obnum});
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iter_mode_ind = prmode+(obmode-1)*p.probe_modes;
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probe = p.probes(:,:,1,prmode);
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if check_option(p, 'use_gpu')
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probe = utils.Garray(probe);
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end
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if strcmpi(p.prop_regime, 'farfield')
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% in farfield is the probe and object shift equivalent in nearfield not anymore !!
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probe = imshift_fft(probe,sub_px_shift(p.scanidxs{p.scanID},[2,1]));
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end
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if Nlayers > 1 && p.simulation.thickness > 0
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% assume that the provided probe is in center plane of the sample
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probe = prop_free_nf(probe, p.lambda, -p.simulation.thickness/2, p.dx_spec(1));
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end
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if any(p.simulation.sample_rotation_angles(1:2))
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% propagate the probe to the tilted plane
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probe = fwd_propag_fun(probe);
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end
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if p.simulation.thickness == 0
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% thin object
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obj = prod(p.simulation.obj{obnum}(:,:,obmode,:),4);
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else
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obj = p.simulation.obj{obnum}(:,:,obmode,:);
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end
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obj_proj = core.get_projections(p, obj(:,:,obmode,1) , p.scanID);
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proj = probe .* obj_proj;
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if p.simulation.thickness > 0
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% thick object
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[~,H] = prop_free_nf(probe, p.lambda, p.simulation.thickness / (Nlayers-1), p.dx_spec);
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for layer = 2:Nlayers
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if Nlayers > 2 && utils.verbose >= 0; utils.progressbar(layer-1, Nlayers-1); end
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proj = ifft2(H.*fft2(proj));
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obj_proj = core.get_projections(p, p.simulation.obj{obnum}(:,:,obmode,layer), p.scanID, obj_proj);
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if strcmpi(p.prop_regime, 'nearfield')
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% in farfield is the probe and object shift equivalent in nearfield not anymore !!
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obj_proj = imshift_fft(obj_proj .* win,-sub_px_shift(p.scanidxs{p.scanID},[2,1])) ./ win;
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end
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proj = proj .* obj_proj;
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end
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else
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proj = bsxfun(@times, probe, obj_proj);
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end
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iter(:,:,:,iter_mode_ind) = proj;
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end
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end
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if any(p.simulation.sample_rotation_angles)
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% perform propagation back to the plane parallel with detector
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iter = back_propag_fun(iter);
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end
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%% create data
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if check_option(p, 'prop_regime', 'nearfield')
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diffraction = abs(prop_free_nf(iter, p.lambda, p.z, p.dx_spec)).^2;
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elseif p.simulation.prop_from_focus
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% calculate intensities
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diffraction = abs(prop_free_nf(ifftshift_2D(fft2(fftshift_2D(iter))), p.lambda, -p.simulation.prop_from_focus, p.ds)).^2;
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else% standard farfield propagation
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diffraction = fftshift_2D(abs(fft2(iter)).^2);
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end
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diffraction = sum(diffraction,4);
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%% add incoherence-like blur
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if p.simulation.incoherence_blur
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diffraction = utils.imgaussfilt3_conv(diffraction, [p.simulation.incoherence_blur,p.simulation.incoherence_blur,0]);
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verbose(3,'- Adding incoherence blur %3.2gpx', p.simulation.incoherence_blur);
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end
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%% add noise
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if ~isinf(p.simulation.photons_per_pixel)
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illum_sum = sum(diffraction(:));
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% calculate the total number of photons per scan
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total_dose = p.simulation.photons_per_pixel * prod(p.object_size-p.asize);
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% calculate correction of the intensity
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corr_ratio = sum(total_dose) / illum_sum;
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% set identical number of photons to diffr. pattern
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diffraction = diffraction * corr_ratio;
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p.simulation.probe = p.simulation.probe * sqrt(mean(corr_ratio));
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verbose(3,'- Adding Poisson noise');
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% add noise, it is some faster approximation
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diffraction = randpoisson(diffraction);
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else
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% keep the values close to real X-ray data
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max_value = 1e3;
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corr_ratio = max_value / max(diffraction(:));
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diffraction = diffraction * corr_ratio;
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p.simulation.probe = p.simulation.probe * sqrt(corr_ratio);
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verbose(3,'- No noise added');
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end
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if check_option(p, 'use_gpu')
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diffraction = gather(diffraction);
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p.simulation.probe = gather(p.simulation.probe);
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for ii = 1:p.numscans
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p.simulation.obj{ii} = gather(p.simulation.obj{ii});
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end
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end
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detStorage.data = double(diffraction);
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detStorage.mask = true(size(diffraction));
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p.positions = positions_0;
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end
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