Alternative to dec2hex in MATLAB? - matlab

Question

I am using dec2hex up to 100 times in MATLAB. Because of this, the speed of code decreases. for one point I am using dec2hex 100 times. It will take 1 minute or more than it. I have do the same for 5000 points. But because of dec2hex it will take hours of time to run. So how can I do hexadecimal to decimal conversion optimally? Is there any other alternative that can be used instead of dec2hex?
As example:
%%Data[1..256]: can be any data from
for i=1:1:256
Table=dec2hex(Data);
%%Some permutation applied on Data
end;
Here I am using dec2hex more than 100 times for one point. And I have to use it for 5000 points.
Data =
Columns 1 through 16
105 232 98 250 234 216 98 199 172 226 250 215 188 11 52 174
Columns 17 through 32
111 181 71 254 133 171 94 91 194 136 249 168 177 202 109 187
Columns 33 through 48
232 249 191 60 230 67 183 122 164 163 91 24 145 124 200 142
This kind of data My code will use.

Answer 1

Function calls are (still) expensive in MATLAB. This is one of the reasons why vectorization and pseudo-vectorization is strongly recommended: processing an entire array of N values in one function call is way better than calling the processing function N times for each element, thus saving the N-1 supplemental calls overhead.
So, what you can do? Here are some non-mutually-exclusive choices:
Profile your code first. Just because something looks like the main culprit for execution time disasters, it isn't necessarily it. Type profview in your command window, chose the script that you want to run, and see where are the hotspots of your code. Choose to optimize those hotspots rather than your initial guesses.
Try faster functions. sprintf is usually fast and flexible:
Table = sprintf('%04X\n', Data);
(and — if you dive into the function code with edit dec2hex — you'll see that in some cases dec2hex actually calls sprintf).
Reduce the number of function calls. Suppose you have to build the table for the 100 datasets of different lengths, that are stored in a cell array:
DataSet = cell(1,100);
for k = 1:100
DataSet{k} = fix(1000*rand(k,1));
end;
The idea is to assemble all the numbers in a single array that you convert at once:
Table = dec2hex(vertcat(DataSet{:}));
Mind you, this is done at the expense of using supplemental memory for assembling the partial inputs in a single one — it's not always convenient to do that.
All the variants above. Okay, this point is not actually a point. :-)