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50 lines
1.8 KiB
Matlab
50 lines
1.8 KiB
Matlab
% APPLY_BINNING apply binning / upsampling on all relevant parameters except data and mask
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%
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% p = apply_binning(p, bin_data)
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%
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% ** p p structure
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% ** binning if binning > 1, then data are binned , if binning < 1, data will be upsampled
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% returns:
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% ++ p p structure
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%
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function p = apply_binning(p, binning)
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% apply binning / upsampling on all relevant parameters except data and mask
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if binning > 0
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assert(all(rem(p.asize, binning)==0), 'Array size cannot be divided for binning')
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end
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% Modify variables for binning
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p.ds = p.ds*binning;
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if check_option(p,'prop_regime', 'farfield')
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p.object_size = p.object_size + ( 1/binning-1)*p.asize ;
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for ii = 1:p.numobjs
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p.object{ii} = utils.crop_pad(p.object{ii},p.object_size(ii,:)); % crop_pad is better when if the binned reconstruction is loaded from file as an initial guess
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end
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p.asize = p.asize/binning;
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%% always assume that no binning was applied on the provided probes
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p.probe_initial = utils.crop_pad( p.probe_initial, p.asize);
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p.probes = utils.crop_pad( p.probes, p.asize);
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else
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p.object_size = ceil(p.object_size / binning);
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for ii = 1:p.numobjs
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p.object{ii} = utils.interpolateFT(p.object{ii},p.object_size(ii,:)); % crop_pad is better when if the binned reconstruction is loaded from file as an initial guess
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end
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p.asize = p.asize/binning;
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%% always assume that no binning was applied on the provided probes
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p.probe_initial = utils.interpolateFT( p.probe_initial, p.asize);
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p.probes = utils.interpolateFT( p.probes, p.asize);
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p.dx_spec = p.dx_spec * binning;
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p.positions = p.positions / binning; % in nearfield the pixel size also changes
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end
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end |