integer strings decoding ... speed optimization

1 view (last 30 days)
I have the following problem:
I need decode integer sequences "c" to char string messages "m" by following association:
numpos = 10 % ( = size(c,2)/2)
c = [3 4 1 1 4 2 5 2 3 3,1 1 1 1 2 2 2 3 3 3]
Each row of "c" represents 2*numpos integers, where first numpos parameters encoded position of
types = {'a' 'b@2' 'c@6' 'd@10' 'e@11'}
and second numpos parameters are applied only if type contains character '@' like this:
m = ' c:1@6 d:1@10 a a d:2@10 b:2@2 e:2@11 b:3@2 c:3@6 c:3@6'
My current solution is as follows:
function m = c2m(c,types)
numpos = size(c,2)/2;
F = cellfun(@(f) [' ' f], strrep(types,'@',':%d@'),'unif',0);
m = arrayfun(@(f,k) sprintf(f{1},k),F(c(:,1:numpos)),c(:,numpos+(1:numpos)),'unif', 0);
m = arrayfun(@(i) horzcat(m{i,:}), (1:numlines)', 'unif', 0)
end
and the testing code is as follows:
numlines = 10;
c = repmat([3 4 1 1 4 2 5 2 3 3,1 1 1 1 2 2 2 3 3 3],numlines,1);
types = {'a' 'b@2' 'c@6' 'd@10' 'e@11'};
m = c2m(c,types);
m =
10×1 cell array
{' c:1@6 d:1@10 a a d:2@10 b:2@2 e:2@11 b:3@2 c:3@6 c:3@6'}
{' c:1@6 d:1@10 a a d:2@10 b:2@2 e:2@11 b:3@2 c:3@6 c:3@6'}
{' c:1@6 d:1@10 a a d:2@10 b:2@2 e:2@11 b:3@2 c:3@6 c:3@6'}
{' c:1@6 d:1@10 a a d:2@10 b:2@2 e:2@11 b:3@2 c:3@6 c:3@6'}
{' c:1@6 d:1@10 a a d:2@10 b:2@2 e:2@11 b:3@2 c:3@6 c:3@6'}
{' c:1@6 d:1@10 a a d:2@10 b:2@2 e:2@11 b:3@2 c:3@6 c:3@6'}
{' c:1@6 d:1@10 a a d:2@10 b:2@2 e:2@11 b:3@2 c:3@6 c:3@6'}
{' c:1@6 d:1@10 a a d:2@10 b:2@2 e:2@11 b:3@2 c:3@6 c:3@6'}
{' c:1@6 d:1@10 a a d:2@10 b:2@2 e:2@11 b:3@2 c:3@6 c:3@6'}
{' c:1@6 d:1@10 a a d:2@10 b:2@2 e:2@11 b:3@2 c:3@6 c:3@6'}
The code is still too slow for me, I am looking for any speed up. In this case the most significant fraction of CPU time is spent at built-in function "sprintf".
Typical realistic sizes of problem are:
numpos ~ 30 ... 60
numlines ~ 1e4 ... 1e5
Any idea?

Accepted Answer

Michal
Michal on 15 Nov 2017
Edited: Michal on 15 Nov 2017
Probably fastest and simplest solution, I found so far ... using latest new Matlab (>= R2016b) features, see function insertBefore and string datatype.
function m = c2m(c,types)
types = string(types);
numpos = size(c,2)/2;
a = c(:,1:numpos);
b = c(:,(numpos+1):end);
m = types(a);
m = insertBefore(m,"@", ":" + b);
m = join(m,2);
end
  2 Comments
Jan
Jan on 15 Nov 2017
Does this consider that some types as "a" do not get an element of b?
Michal
Michal on 15 Nov 2017
I am not sure, what do you mean exactly. Please clarify your question.

Sign in to comment.

More Answers (1)

Jan
Jan on 13 Nov 2017
Edited: Jan on 13 Nov 2017
[EDITED] Consider all rows of c:
function m = c2m(c,types)
[s1, s2] = size(c);
numpos = s2 / 2;
m = cell(s1, 1);
typesF = strrep(types, '@', ':%d@'); % types to format specifiers
hasNum = ~strcmp(types, typesF); % true if the type has a '%d'
for im = 1:s1
c1 = c(im, 1:numpos);
c2 = c(im, numpos+1:end);
FmtSpec = sprintf(' %s', typesF{c1}); % Complete list of format specs
m{im} = sprintf(FmtSpec, c2(hasNum(c1))); % All c2, if c1 has a number spec
end
end
UNTESTED - I have no Matlab currently.
  4 Comments
Michal
Michal on 14 Nov 2017
Edited: Michal on 14 Nov 2017
FmtSpec = CStr2String(typesF{c1}, ' ', 'noTrail');
should be
FmtSpec = CStr2String(typesF(c1), ' ', 'noTrail');
But the speed up with MEX file is only about a few percent.
Michal
Michal on 14 Nov 2017
Edited: Michal on 15 Nov 2017
Jan, thanks a lot for your help. Your code is very good. Especially the fact, that the for-loop is possible to simple transform to parfor-loop to get some additional speed-up without any re-programming.

Sign in to comment.

Categories

Find more on Get Started with MATLAB in Help Center and File Exchange

Tags

Products

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!