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ptycho/+detector/+virtual/private/randpoisson.m

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+function out=randpoisson(inarray,thresh);␍% function out=randpoisson(inarray,thresh);␍% outputs an array of poisson-distributed numbers with mean equal to inarray␍% For inarray values above the threshold thresh (default=32),␍%  use a quick-and-dirty version of the gaussian method,␍%  but with negatives clipped to zero␍% J.R. Fienup 10/22/99␍␍␍if nargin <  1, ␍    error('Requires at least one input argument.'); ␍end␍␍if exist('thresh')~=1, thresh=32; end␍␍out=inarray;␍% High-count pixels - use Gaussian approach␍gtthresh=find(inarray>thresh);␍if ~isempty(gtthresh),␍	out(gtthresh)=inarray(gtthresh) + sqrt(inarray(gtthresh)).*randn(size(inarray(gtthresh)));␍	out(gtthresh)=round(max(0,out(gtthresh)));␍end␍% Low-count pixels - this goes into the counting-experiment method␍␍ltthresh=find(inarray<=thresh);␍if ~isempty(ltthresh)␍	lamda=inarray(ltthresh); % segregate low-value pixels to speed computation␍	% Now dealing with a 1-D column vector that will merge into n-D array out later on␍	%Initialize r to zero.␍	r = zeros(size(lamda));  % output array for ltthresh pixels␍	p = zeros(size(lamda));␍	ind = true(size(lamda));␍	    ␍    while any(ind)␍	    p(ind) = p(ind) - log(rand(length(ind),1));  % note, do repeatedly calculate over all of lamda␍	    ind = find(p < lamda); % Q: does this k index over ␍        r(ind) = r(ind) + 1;␍    end␍␍	    ␍	% Return NaN if lamda is not positive -- to do this, un-comment what follows (gives zero now).␍	␍% 	tmp = NaN;␍% 	if any(any(any(lamda <= 0)));␍% 	    if prod(size(lamda) == 1),   % i.e., a single pixel?␍% 	        r = tmp(ones(size(lamda)));␍% 	    else␍% 	        k = find(lamda <= 0);␍% 	        r(k) = tmp(ones(size(k)));␍% 	    end␍% 	end␍␍	out(ltthresh)=r;  % Merge low-value-pixel results with large-value-pixel results␍	␍end; % of if length(ltthresh)>0␍␍end␍␍