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124 lines
4.2 KiB
Matlab
124 lines
4.2 KiB
Matlab
% GET_INTEGRATION_MATRIX Generate sparse integration matrix that sums up
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% values according to the provided integration mask
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%
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%
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% int_matrix = get_integration_matrix(mask)
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%
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% Inputs:
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% **mask - 2D integer array, 0 = ignored regions, 1:max(mask) are different sectors that will be summed separatelly
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% Outputs:
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% ++int_matrix - 2D sparse matrix
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%
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%
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%%%%%%%%%%%%%%%%%%%%% HOW TO USE %%%%%%%%%%%%%%%%%%%%%%%%%%%
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%
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% % create some data
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% img = single(imread('cameraman.tif'));
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% img = repmat(img, 1,1,10); % just add there 3rd dimension
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% Np = size(img);
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%
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% %% define parameters of the integration matrix
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% Nrad = 20;
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% Nsec = 30;
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% center_pos = Np/2-30;
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%
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%
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% %% generate radial and sector masks, needs to be modified if center != Np/2
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% [mask, radial_mask, sector_mask] = get_radial_integration_mask(Np, Nrad, Nsec, center_pos);
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%
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% %% check the generated sector mask
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% figure(1)
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% imagesc(mask); axis off image
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% title('Radial & Angular sectors')
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% colormap(hsv)
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% drawnow
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%
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% % generate the integration 2D sparse matrix
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% T = get_integration_matrix(mask);
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%
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%
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% %% perform sparse matrix based integration
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% tic
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% img_sum = single(reshape((T*reshape(double(img), prod(Np(1:2)), [])), Nrad,Nsec, []));
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% toc
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%
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% %% perform matlab based integration for comparison
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% tic
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% img_sum_0 = zeros(Nrad,Nsec, size(img,3));
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% for nz = 1:size(img,3)
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% im = img(:,:,nz);
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% for i = 1:Nrad
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% m = radial_mask == i;
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% for j = 1:Nsec
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% img_sum_0(i,j,nz) = sum(im( m & sector_mask == j ));
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% end
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% end
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% end
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% toc
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%
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%
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% % show the first frame to check that the methods are identical
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% figure
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% subplot(1,2,1)
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% imagesc(img_sum_0(:,:,1)); axis image
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% title('Matlab')
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% subplot(1,2,2)
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% imagesc(img_sum(:,:,1)); axis image
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% title('Sparse matrix')
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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 int_matrix = get_integration_matrix(mask)
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N = max(mask(:));
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Np = size(mask);
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int_matrix = zeros(prod(Np),2);
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ind_start = 1;
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for id = 1 : max(mask(:))
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[i,j] = find(mask == id);
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ind_end = ind_start + length(i)-1;
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int_matrix(ind_start:ind_end,:) = [id*ones(length(i),1),i+(j-1)*Np(1)];
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ind_start = ind_end + 1;
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end
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% convert to sparse matrix
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int_matrix = sparse(int_matrix(1:ind_end,1),int_matrix(1:ind_end,2),ones(ind_end,1), N, prod(Np));
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end
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