Added fastcounts, which much faster than histcounts especially for sorted data

function counts = fastcounts(times,tedges)

%FASTCOUNTS Histogram of array of times put in bins with edges tedges

%   For longish arrays it's much faster than hisctounts and uses only a

%   fraction of its memory; operating on sorted times are where it shines

%   but it still is faster in  unsorted ones. 

%   The tedges can be non-uniformly spaced but the algorithm doesn't

%   rescale counts based on width: if you want that use histcounts

if (~issorted(times))

    times = sort(times);

end

Nedges = length(tedges);

Nbins = length(tedges)-1;

Nphot = length(times);

counts = zeros(size(tedges));

counts = counts(1:Nbins);

% It appears matlab is faster with doubles anyway, we can take the

% negligible hit in memory

% counts = zeros(size(tedges),'int16');

% counts = counts(1:Nbins);

% if (Nphot<intmax('int16'))

%     counts = zeros(size(counts),'int16');

% elseif (Nphot<intmax('int32'))

%     counts = zeros(size(counts),'int32');

% elseif (Nphot<intmax('int64'))

%     counts = zeros(size(counts),'int64');

% else

%     disp(['The length of times is greater than ',num2str(intmax('int64')),', nothing will work!'])

% end

j = 1;

i = 1;

while i < Nedges

    while (j<=Nphot && times(j)<tedges(i+1))

        counts(i) = counts(i)+1;

        j = j+1;

    end

    i = i+1;

end

end

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