finding a minimum from multiple matricies

Hi everybody, I have a few large matricies of equal size. At each location, I would like to find minimum and its index. Note, essentially an index in this case would correpsond to a particular matrix. Say I have two matricies first=[2 3 4] and second=[4 5 2] Then at location (1,1) the minimum would be 2 with index=1 as to correcpond to the first matrix. I am wondering if there is a way to do it without runing double for loop? Thanks!

[Azzi Abdelmalek]

how many matrix do you want to compare?

Answer 1

[Andrei Bobrov]

Let your three matrices in 3D array M

M = randi(234,5,5,3); % initial array
[v,ii] = min(M,[],3);

Answer 2

[Sean de Wolski]

first=[2 3 4];
second=[4 5 2]
val = min(first,second);
idx = (second==val)+1

Answer 3

[Azzi Abdelmalek]

A={rand(4,5),rand(4,5),rand(4,5),rand(4,5)};
[c,idx1]=cellfun(@(x) min(x(:)),A)
[value,matnum]=min(c)    % value = minimum and matnum= matrix number
idx=idx1(matnum)         
nA=4                      % nA, each matrix is nA x mA
n=mod(idx,nA)             
if n==0
  n==nA
end
m=ceil(idx/nA)           % the location is (n,m)

Answer 4

[Image Analyst]

Here's a demo for 4 small matrices. You can adapt it for more matrices, and for larger matrices:

format compact;
m1 = rand(5,5)
m2 = rand(5,5)
m3 = rand(5,5)
m4 = rand(5,5)
% Now we have our several "large" matrixes.
% Concatenate them
m3D = cat(3, m1, m2, m3, m4);
% Find the min and a map of what matrix it occurred in.
[min2DImage matrixWhereItOccurs] = min(m3D, [], 3)

Results:

m1 =
Columns 1 through 3
       0.683715572408358         0.640717922965926         0.740032327987778
       0.132082955713563         0.328814214756803         0.234826914747904
       0.722724539656766         0.653812022595774         0.734957541696052
       0.110353480642349         0.749131463103519         0.970598525086614
       0.117492852151833         0.583185731454876         0.866930291751916
Columns 4 through 5
      0.0862345298634963         0.789363943641905
       0.366436616319199         0.367652918437877
       0.369198804330018         0.206027859505195
       0.685028472661609        0.0866665473955323
       0.597941635383889         0.771933917099107
m2 =
Columns 1 through 3
        0.20567452146476          0.48448037239818         0.237373019705579
       0.388271631047802         0.151845525116267         0.530872257027928
       0.551778531957227         0.781931966588002        0.0914987313394122
         0.2289532520231         0.100606322362422         0.405315419880591
       0.641940620399187         0.294066333758628         0.104846247115757
Columns 4 through 5
       0.112283962156027         0.432484993970361
       0.784427890743913          0.69475219461794
       0.291570317906931         0.758099275289454
       0.603533438750887         0.432642326147101
       0.964422667215901         0.655498039803537
m3 =
Columns 1 through 3
       0.109755050723052         0.487603775433924         0.673294914108653
       0.933759848385332         0.768958264058869         0.429564459251853
       0.187460806421687         0.396006745217875         0.451739234904736
       0.266178838907639         0.272938794123691         0.609857169290216
       0.797830260211597         0.037234634070328        0.0594032968582772
Columns 4 through 5
       0.315811438338866        0.0923523387192016
       0.772722130862935       0.00782029356933489
       0.696432989006095         0.423109385164167
        0.12533218110918         0.655573174937914
       0.130151450389424         0.722922524692024
m4 =
Columns 1 through 3
       0.531209293582439        0.0985940927109977         0.316428999146291
       0.108817938273045         0.142027248431928         0.217563309422821
       0.631766373528489         0.168251298491528         0.251041846015736
       0.126499865329303         0.196248922256955         0.892922405285977
       0.134303304313575         0.317479775149435         0.703223224556291
Columns 4 through 5
       0.555737942719387         0.706715217696931
       0.184433667757653         0.557788966754876
       0.212030842532321         0.313428989936591
      0.0773468081126768         0.166203562902151
       0.913800410779568         0.622497259279895
min2DImage =
Columns 1 through 3
       0.109755050723052        0.0985940927109977         0.237373019705579
       0.108817938273045         0.142027248431928         0.217563309422821
       0.187460806421687         0.168251298491528        0.0914987313394122
       0.110353480642349         0.100606322362422         0.405315419880591
       0.117492852151833         0.037234634070328        0.0594032968582772
Columns 4 through 5
      0.0862345298634963        0.0923523387192016
       0.184433667757653       0.00782029356933489
       0.212030842532321         0.206027859505195
      0.0773468081126768        0.0866665473955323
       0.130151450389424         0.622497259279895
matrixWhereItOccurs =
   3     4     2     1     3
   4     4     4     4     3
   3     4     2     4     1
   1     2     2     4     1
   1     3     3     3     4

Answer 5

[jenka]

You, guys, are soooooooooooooo great! Awesome! and thank you!