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91 lines
4.2 KiB
Matlab
91 lines
4.2 KiB
Matlab
% BINNING_2D - bin data along first two axis,
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% x = binning_2D(x, binning, centered)
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%
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% Inputs:
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% **x - original array, upsampling will be performed only along the first two axis, array size has to be dividable by binning size
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% **binning - scalar or (2,1) array, positive integer binning factor
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% *Optional*:
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% **centered - default false, shift the binning by binning/2 offset
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%
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% Outputs:
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% ++x - binned array
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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 x = binning_2D(x, binning, centered)
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if all(binning <= 1); return ; end
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if nargin < 3
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centered = false;
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end
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Npix = [size(x,1), size(x,2), size(x,3)];
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if isscalar(binning); binning = repmat(binning, 1,2); end
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binning = reshape(binning,1,[]);
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if all(Npix(1:2) >= binning(:))
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% faster but less general version
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if centered
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% it will be slower due to memory copy
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x = x(ceil(binning(1)/2):end-ceil(binning(1)/2)-1, ceil(binning(2)/2):end-ceil(binning(2)/2)-1,:);
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Npix(1:2) = Npix(1:2) - binning;
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end
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if any(~math.isint(Npix(1:2)./binning))
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% is the array cannot be easily split for binning, crop it
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% it will be slower due to memory copy
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Npix(1:2) = floor(Npix(1:2)./binning) .* binning;
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x = x(1:Npix(1),1:Npix(2),:);
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end
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x = reshape(x,binning(1), Npix(1)/binning(1), binning(2), Npix(2)/binning(2), Npix(3));
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x = squeeze(sum(sum(x,1),3));
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x = x / prod(binning(1:2));
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if centered
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x = padarray(x, [1,1], 'replicate', 'post'); % account for the removed pixels to keep the size
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end
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else
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x = convn(single(x), ones(binning, 'single'), 'same');
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norm = binning.^2;
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ind = {ceil(binning(1)/2):binning(1):Npix(1), ceil(binning(2)/2):binning(2):Npix(2)};
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% avoid issues with void dimensions
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for i = find(Npix == 1)
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ind{i} = ':';
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norm = norm / binning(i); %% avoid summing up by convolution
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end
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x = x(ind{:},:) / norm;
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end
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end |