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% [volume_new, update] = apply_lamino_constraints(volume, mask, lamino_angle , low_freq_protection, constrain_fun, Niter)
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% apply laminography constraints in the real space and try to refill missing cone in laminography by provided prior
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% knowledge
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% Inputs:
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% **volume - (3D array) represeting the refined volume in realspace
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% **mask - (vector, array), mask pushing pixels where mask < 1 towards zero. Can be either 3D or only for example along 3r axis ie size(mask) = [1,1,Nlayers]
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% **lamino_angle - (scalar), laminography angle from 0 to 90degrees, 90 == classical tomo, it is used to calculate the missing cone
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% **low_freq_protection - (bool), used to protect in the fourier space the central region, ie low spatial frequncies. Important when multiscale approach is used
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% **constrain_fun - anonymous function providing constrains such as positivity or material range limits
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% **Niter - number of optimization iterations
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% *returns*
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% ++volume_new refined object
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% ++update (norm(volume) - norm(update_new)) / norm(volume)
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%
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% Example:
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% see template_tomo_recons_lamino.m for working example
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%*-----------------------------------------------------------------------*
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%| |
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%| Except where otherwise noted, this work is licensed under a |
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%| Creative Commons Attribution-NonCommercial-ShareAlike 4.0 |
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%| International (CC BY-NC-SA 4.0) license. |
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%| |
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%| Copyright (c) 2018 by Paul Scherrer Institute (http://www.psi.ch) |
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%| |
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%| Author: CXS group, PSI |
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%*-----------------------------------------------------------------------*
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% You may use this code with the following provisions:
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%
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% If the code is fully or partially redistributed, or rewritten in another
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% computing language this notice should be included in the redistribution.
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%
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% If this code, or subfunctions or parts of it, is used for research in a
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% publication or if it is fully or partially rewritten for another
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% computing language the authors and institution should be acknowledged
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% in written form in the publication: “Data processing was carried out
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% using the “cSAXS matlab package” developed by the CXS group,
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% Paul Scherrer Institut, Switzerland.”
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% Variations on the latter text can be incorporated upon discussion with
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% the CXS group if needed to more specifically reflect the use of the package
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% for the published work.
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%
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% A publication that focuses on describing features, or parameters, that
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% are already existing in the code should be first discussed with the
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% authors.
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%
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% This code and subroutines are part of a continuous development, they
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% are provided “as they are” without guarantees or liability on part
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% of PSI or the authors. It is the user responsibility to ensure its
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% proper use and the correctness of the results.
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function [volume_new, update] = apply_lamino_constraints(volume, mask, lamino_angle , low_freq_protection, value_max, value_min, Niter, TV_lambda)
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import utils.Garray
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Npix = size(volume);
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fft_mask = lamino.get_lamino_fourier_mask( Npix, lamino_angle, true);
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fft_mask = Garray(fft_mask);
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if low_freq_protection
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% avoid modification of the low spatial frequencies that were
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% already refined
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fft_mask = fftshift(fft_mask);
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for i = 1:3
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grid{i} = ceil(Npix(i)/2)+[-ceil(Npix(i)/8):floor(Npix(i)/8)];
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end
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fft_mask(grid{:}) = 0;
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fft_mask = fftshift(fft_mask);
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end
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volume = Garray(volume);
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fft_split = 1;
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for iter = 1:Niter
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utils.progressbar(iter,Niter)
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volume_new = volume;
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%volume_new = regularization.local_TV3D_chambolle(volume_new, 1e-7, 10);
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volume_new = regularization.local_TV3D_chambolle(volume_new, TV_lambda, 10);
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% positivity constraint
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volume_new = arrayfun(@clip_range,volume_new, value_max, value_min, mask);
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%% go to the Fourier space
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fvolume = (math.fftn_partial(Garray(volume), fft_split));
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fvolume_new = (math.fftn_partial(Garray(volume_new), fft_split));
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%% merge updated and original dataset in the fourier space
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%% use overrelaxation of the constraint to get faster convergence
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relax = 1.5;
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regularize = 0.0;
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fvolume = arrayfun(@relax_contraint,fvolume, fvolume_new, fft_mask, relax, regularize);
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clear fvolume_new
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%% back to the real space
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volume_new = real(math.ifftn_partial(Garray(fvolume), fft_split));
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clear fvolume
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% get difference in update
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update = gather(norm(volume(:)-volume_new(:)) ./ norm(volume(:)));
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volume = volume_new;
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end
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volume = gather(volume);
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end
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% auxiliary function for fast execution on GPU
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function fvolume = relax_contraint(fvolume, fvolume_new, fft_mask, relax, regularize)
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fvolume = fvolume .* ( 1- relax.*fft_mask) + fvolume_new .* relax.*fft_mask;
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fvolume = fvolume .* (1 - regularize.*fft_mask);
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end
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function array = clip_range(array, max_val, min_val, mask)
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array = max(min_val, min(max_val, array)) .* mask;
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end
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@@ -0,0 +1,79 @@
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% weight_sino = estimate_reliability_region(complex_projection, probe_size, subsample)
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% Estimates the region where the complex projections are good enough to be unwrapped. Assumes that outside
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% of the measured FOV the amplitude of the object will be zero. This assumes that ptychography reconstruction
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% did not add any values, due to those pixels never been reached by any probe element. Then the region is reduced
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% by half the probe size using something akin to erosion. This function is only useful if the FOV is not square,
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% such as the case of the elliptical FOV of laminography.
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%
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% Pseudo code example:
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% weights = imerode(abs(object) > 0, ones(probe_size/2))
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%
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% Inputs:
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% **complex_projection - (3D array) complex valued reconstructions
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% **probe_size - (int, int) size of the illumination probe
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% **subsample - (int) subsample the resulting array to save memory
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% Outputs:
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% ++weight_sino - weights, 1 for full quality, 0<=W<1 for poor regions
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%*-----------------------------------------------------------------------*
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%| |
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%| Except where otherwise noted, this work is licensed under a |
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%| Creative Commons Attribution-NonCommercial-ShareAlike 4.0 |
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%| International (CC BY-NC-SA 4.0) license. |
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%| |
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%| Copyright (c) 2018 by Paul Scherrer Institute (http://www.psi.ch) |
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%| |
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%| Author: CXS group, PSI |
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%*-----------------------------------------------------------------------*
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% You may use this code with the following provisions:
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%
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% If the code is fully or partially redistributed, or rewritten in another
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% computing language this notice should be included in the redistribution.
|
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%
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% If this code, or subfunctions or parts of it, is used for research in a
|
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% publication or if it is fully or partially rewritten for another
|
||||
% computing language the authors and institution should be acknowledged
|
||||
% in written form in the publication: “Data processing was carried out
|
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% using the “cSAXS matlab package” developed by the CXS group,
|
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% Paul Scherrer Institut, Switzerland.”
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% Variations on the latter text can be incorporated upon discussion with
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% the CXS group if needed to more specifically reflect the use of the package
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% for the published work.
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%
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% A publication that focuses on describing features, or parameters, that
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% are already existing in the code should be first discussed with the
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% authors.
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%
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% This code and subroutines are part of a continuous development, they
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% are provided “as they are” without guarantees or liability on part
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% of PSI or the authors. It is the user responsibility to ensure its
|
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% proper use and the correctness of the results.
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function weight_sino = estimate_reliability_region(complex_projection, probe_size, subsample)
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% simple reliability estimation based on amplitude of the
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% reconstruction
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Npix = size(complex_projection);
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Npix_new = ceil(Npix(1:2)/subsample/2)*2;
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%% SOLVE THE PROBLEM IN LOW RESOLUTION
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weight_sino = tomo.block_fun(@utils.interpolateFT, complex_projection,Npix_new, struct('use_GPU', false, 'use_fp16', false));
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probe_size = round(probe_size .* Npix_new ./ Npix(1:2));
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weight_sino =abs(weight_sino);
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weight_sino = single(weight_sino > 0.1*quantile(weight_sino(:),0.9));
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%% only CPU is supported -> gather and move abck to GPU afterwards
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weight_sino = gpuArray(utils.imcrop_outliers(gather(weight_sino))); % leave only single largest compact object
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[Y,X] = meshgrid(-ceil(probe_size(1)/2):floor(probe_size(1)/2), -ceil(probe_size(2)/2):floor(probe_size(2)/2));
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probe = (X/probe_size(1)*2).^2+(Y/probe_size(2)*2).^2 < 1;
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kernel = probe/sum(probe(:));
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weight_sino = convn(weight_sino, kernel , 'same');
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weight_sino = weight_sino > 0.95;
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weight_sino = uint8(imgaussfilt(single(weight_sino), 1)*255);
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end
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@@ -0,0 +1,65 @@
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% fft_mask = get_lamino_fourier_mask( Npix, lamino_angle, keep_on_GPU)
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% find the missing cone mask based on provided inputs
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% Inputs:
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% **Npix - (3x1 int) volume size
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% **lamino_angle - (scalar), laminography angle from 0 to 90degrees, 90 == classical tomo, it is used to calculate the missing cone
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% **keep_on_GPU - (bool) move the mask to GPU and keep it there
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% *returns*
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% ++fft_mask = mask in the fourier space
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%
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% Example:
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% ifftn(fftn(volume).*fft_mask)
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%*-----------------------------------------------------------------------*
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%| |
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%| Except where otherwise noted, this work is licensed under a |
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||||
%| Creative Commons Attribution-NonCommercial-ShareAlike 4.0 |
|
||||
%| International (CC BY-NC-SA 4.0) license. |
|
||||
%| |
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%| Copyright (c) 2018 by Paul Scherrer Institute (http://www.psi.ch) |
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%| |
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%| Author: CXS group, PSI |
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%*-----------------------------------------------------------------------*
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% You may use this code with the following provisions:
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%
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% If the code is fully or partially redistributed, or rewritten in another
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||||
% computing language this notice should be included in the redistribution.
|
||||
%
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% If this code, or subfunctions or parts of it, is used for research in a
|
||||
% publication or if it is fully or partially rewritten for another
|
||||
% computing language the authors and institution should be acknowledged
|
||||
% in written form in the publication: “Data processing was carried out
|
||||
% using the “cSAXS matlab package” developed by the CXS group,
|
||||
% Paul Scherrer Institut, Switzerland.”
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||||
% Variations on the latter text can be incorporated upon discussion with
|
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% the CXS group if needed to more specifically reflect the use of the package
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||||
% for the published work.
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||||
%
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||||
% A publication that focuses on describing features, or parameters, that
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||||
% are already existing in the code should be first discussed with the
|
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% authors.
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||||
%
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||||
% This code and subroutines are part of a continuous development, they
|
||||
% are provided “as they are” without guarantees or liability on part
|
||||
% of PSI or the authors. It is the user responsibility to ensure its
|
||||
% proper use and the correctness of the results.
|
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function fft_mask = get_lamino_fourier_mask( Npix, lamino_angle, keep_on_GPU)
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if nargin < 3
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keep_on_GPU = false;
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end
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for i = 1:3
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grid{i} = fftshift(linspace(-1,1,Npix(i)))';
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grid{i} = shiftdim(grid{i},1-i);
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if keep_on_GPU, grid{i} = utils.Garray(grid{i}); end
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end
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fft_mask = get_mask(grid{:}, lamino_angle);
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end
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function fft_mask = get_mask(xgrid, ygrid, zgrid, lamino_angle)
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fft_mask = ceil(atand( abs(zgrid) ./ sqrt(xgrid.^2+ygrid.^2) )) > lamino_angle;
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end
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