Looking-to-cue-sides-and-modulation-of-value-in-OFC/code/support_functions/runlength.m

function [ts_rl] = runlength(ts, ts_sh, plot_flag, time_axis, color_vec, y_offset, alphafill, alphaline)

if nargin<8
if nargin<7
    if nargin <6
        if nargin<5
            if nargin<4
                if nargin<3
                    plot_flag=0;
                end
                if isvector(ts)
                    time_axis=1:length(ts);
                else
                    error('input1 needs to be vector');
                end
            end
            color_vec=[0 0 0];
        end
        y_offset=nan;
    end
    alphafill=.2;
end
alphaline=1;
end
% ts     [Ntimepoints  x 1] contains time series data
% ts_sh  [Ntps x Nshuffles] contains shuffled data

if isrow(ts)
    ts=ts';
end

if ismatrix(ts_sh) && any(size(ts_sh)==length(ts))
    if size(ts_sh,2)==length(ts)
        ts_sh=ts_sh';
    end
else
    error('input2 is not correct in size');
end

ts_p95=prctile(ts_sh,95,2);
ts_ccs=countconsecutiveones(ts_sh>ts_p95);
ts_ccs_p95=prctile(rmnans(ts_ccs(:)),95);
if isnan(ts_ccs_p95); ts_ccs_p95=0; end
[~,~,~,ts_rlen]=countconsecutiveones((ts>ts_p95),0,ts_ccs_p95);
ts_rl=zeros(1,length(ts)); ts_rl(ts_rlen==0)=nan;

if (plot_flag)
    plotmsem(time_axis,ts,color_vec); hold on;
    plotperc(time_axis,ts_sh,[5 95],color_vec,alphafill);
    gyl=get(gca,'YLim');
    if isnan(y_offset); y_offset=min(gyl)+0.01.*diff(gyl); end
    plot(time_axis,y_offset+ts_rl,'color',[color_vec alphaline],'linewidth',5); hold on;
    ylim(gyl);
end