function trialcode
ENGSPD_1       = rand(1812890, 1);
Eng_Spd        = rand(125000, 1);
Speed          = rand(412730, 1);
TIME           = rand(412730, 1);
Time           = rand(125000, 1);
engine_speed_2 = rand(14060, 1);
time_1         = rand(1812890, 1);
time_2         = rand(14060, 1);

save('tmp.mat');
data = load('tmp.mat');

t1 = timeit(@()wtf(ENGSPD_1, Eng_Spd, Speed, TIME, Time, engine_speed_2, time_1, time_2));
t2 = timeit(@()ok(ENGSPD_1, Eng_Spd, Speed, TIME, Time, engine_speed_2, time_1, time_2));
t3 = timeit(@()oker(data));

tmp = ver;
fprintf(['Benchmarking Results, MATLAB %s\n' ...
         '=====================================\n' ...
         'rahnema1:   %0.5f\n' ...
         'excaza:     %0.5f\n' ...
         'excaza (2): %0.5f\n\n' ...
         'Save\\Load overhead intentionally ignored\n'], ...
         tmp.Release, t1, t2, t3);
end

function wtf(ENGSPD_1, Eng_Spd, Speed, TIME, Time, engine_speed_2, time_1, time_2)
speed_whos=[whos('*P*');whos('*p*')];
time_whos=[whos('*T*');whos('*t*')];

name_speed={speed_whos(:).name};
name_time={time_whos(:).name};

sz_speed =reshape([speed_whos(:).size],2,[]).';
sz_time  = reshape([time_whos(:).size],2,[]).';

[ ~,i_time] =sortrows(sz_time);
[ ~,i_speed] =sortrows(sz_speed);

name_speed = name_speed(i_speed);
name_time = name_time(i_time);
data = struct;
for k = 1: numel(name_time)
    eval('data(k).time = eval(name_time{k});data(k).speed = eval(name_speed{k});');
end
end

function ok(ENGSPD_1, Eng_Spd, Speed, TIME, Time, engine_speed_2, time_1, time_2)
% Identify time and speed variable using regular expressions
% Assumes time variables contain 'time' (case insensitive)
% Assumes speed variables contain 'spd', 'sped', or 'speed' (case insensitive)
timevars = whos('-regexp', '[T|t][I|i][M|m][E|e]');
speedvars = whos('-regexp', '[S|s][P|p][E|e]{0,2}[D|d]');

% Pair timeseries and data arrays together. Data is only coupled if
% the number of rows in the timeseries is exactly the same as the
% number of rows in the data array.
timesizes  = vertcat(speedvars(:).size);  % Concatenate timeseries sizes
speedsizes = vertcat(timevars(:).size);  % Concatenate speed array sizes

% Find intersection and their locations in the structures returned by whos
% By using intersect we only get the data that is matched
[sizes, timeidx, speedidx] = intersect(timesizes(:,1), speedsizes(:,1));

% Preallocate structure
ndata = length(sizes);
groupeddata(ndata).time = [];
groupeddata(ndata).speed = [];

% Unavoidable (without saving/loading data) eval loop :|
for ii = 1:ndata
    groupeddata(ii).time  = eval('timevars(timeidx(ii)).name');
    groupeddata(ii).speed = eval('speedvars(speedidx(ii)).name');
end
end

function oker(oldworkspace)
varnames = fieldnames(oldworkspace);

timevars = regexpi(varnames, '.*time.*', 'match', 'once');
timevars(cellfun('isempty', timevars)) = [];
speedvars = regexpi(varnames, '.*spe{0,2}d.*', 'match', 'once');
speedvars(cellfun('isempty', speedvars)) = [];

timesizes = zeros(length(timevars), 2);
for ii = 1:length(timevars)
    timesizes(ii, :) = size(oldworkspace.(timevars{ii}));
end
speedsizes = zeros(length(speedvars), 2);
for ii = 1:length(speedvars)
    speedsizes(ii, :) = size(oldworkspace.(speedvars{ii}));
end

[sizes, timeidx, speedidx] = intersect(timesizes(:,1), speedsizes(:,1));

ndata = length(sizes);
groupeddata(ndata).time = [];
groupeddata(ndata).speed = [];

for ii = 1:ndata
    groupeddata(ii).time  = oldworkspace.(timevars{timeidx(ii)});
    groupeddata(ii).speed = oldworkspace.(speedvars{speedidx(ii)});
end
end