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120 lines
5.1 KiB
Matlab
120 lines
5.1 KiB
Matlab
% RADIATION_DAMAGE_ESTIMATION Plot SVD filtered curved of the vertical fluctuations
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% tomo invariant to shown if there was radiation damage
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%
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% radiation_damage_estimation(object, par, varargin)
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%
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% Inputs:
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% **object - complex valued projections
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% **par - tomography paramter structure
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% **varargin - see the code
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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) 2017 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 radiation_damage_estimation(object, par, varargin)
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import plotting.*
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import math.*
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parser = inputParser;
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parser.addParameter('N_SVD_modes', 1 , @isnumeric )
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parser.addParameter('smoothing', 15 , @isnumeric )
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parser.addParameter('logscale', true , @islogical ) % threshold for mask estimation
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parser.addParameter('invariant', 'derivative' , @isstr ) % threshold for mask estimation
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parser.addParameter('vert_range', [] , @isnumeric ) % threshold for mask estimation
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parser.parse(varargin{:})
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r = parser.Results;
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if ~isempty(r.vert_range)
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object = object((max(1,r.vert_range(1)):min(end,r.vert_range(end))),:,:);
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end
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switch r.invariant
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case 'phase'
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%% standard vertical mass fluctuation
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phase_diff = tomo.get_phase_gradient(object, 2,0.5);
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phase = -tomo.unwrap2D_fft(phase_diff, 2, par.air_gap);
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invariant = max(0,squeeze(sum(phase,2)));
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case 'derivative'
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%% vertical derivative fluctuation
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phase_diff_vert = math.get_phase_gradient_1D(object, 1,1);
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invariant = squeeze(sum(phase_diff_vert,2));
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end
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% smoothing in the time domain to remove outliers
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mass_filt = medfilt2(invariant,[1,floor(r.smoothing/2)*2+1], 'symmetric');
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figure(5);
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subplot(3,1,1)
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imagesc(invariant)
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axis tight xy
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colormap(franzmap)
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caxis(sp_quantile(invariant, [0.01, 0.99], 10))
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title(sprintf('Vertical mass derivative S%05d - S%05d',par.scanstomo(1),par.scanstomo(end)))
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xlabel('Projection number')
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grid on
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subplot(3,1,2)
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Navg_slices= 10; % average over last 10 slices
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mass_filt_resid = mass_filt - median(mass_filt(:,end-Navg_slices:end),2);
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imagesc(mass_filt_resid)
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axis tight xy
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if r.logscale
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set(gca, 'xscale', 'log')
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end
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colormap bone
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caxis(sp_quantile(mass_filt_resid, [0.01, 0.99], 10))
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title('Filtered change with respect to median')
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xlabel('Projection number')
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grid on
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subplot(3,1,3)
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[U,S,V] = svd(mass_filt);
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S = S / sqrt(sum(diag(S.^2)));
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plot( V(:,[2:r.N_SVD_modes+1]) * S(2:r.N_SVD_modes+1,2:r.N_SVD_modes+1) )
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if r.logscale
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set(gca, 'xscale', 'log')
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end
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title(sprintf('PCA decomposition - shows changes in the sample, Power=%2.3g%%', 100*sum(diag(S(2:end,2:end)).^2)))
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axis tight
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xlabel('Aprox projection number')
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grid on
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file_png = fullfile(par.output_folder,'Radiation_damage_curve.png');
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disp(['Saving ' file_png])
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end |