How can I apply a random number generator in a nested loop?

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Stephanie Diaz 2017-5-3

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评论： Stephanie Diaz 2017-5-5

Hi all,

I'm new to matlab, but here is my dilemma: I want to select the cells with the highest values in a matrix (A) within a given range (determined by a radius). The selection of the highest value only happens if a given probability (which considers values t) is high enough. To do this, I am reading in a values (t), and applying this to a probability at every iteration ( for a max of 120 values corresponding to 120 iterations). My results, which is a plot of the cell selected every iteration, is a vertical line across the matrix (which does not make sense). I think it may be an issue with the for loop involving the random number generator. I would appreciate any suggestions concerning how to "fix" this, and I hope my description makes some kind of sense. Below is a shortened version of the code:

for i=1:maxtime  % iteration over time steps to the maximum 120 time steps
      xstart = xpos-range; % These are start positions
      ystart = ypos-range; 
      for t=1:120; %iteration over all values 1-120 
  current_t=temp_hourly(t,:); % this updates the value every iteration
prob_thermoreg= current_t-threshold_t; % determines the probability 
rn=rand; % generates random number 
if prob_thermoreg>rn;
%the logic below selects the cell with the highest value
maxtreecover = 0.0;  %find value larger than this
maxx_tree = xstart;
maxy_tree = ystart; 
for jj=1:20  %double the radius set at 10 cells
for ii=1:20  
          if A(ystart + ii,xstart + jj) > maxtreecover; % if the value of A at different ii and jj is greater than max 0.0, select this cell
              maxtreecover = A(ystart + ii,xstart + jj); 
              maxx_tree = xstart + jj;
              maxy_tree = ystart + ii;
          end
  end
  end
   end
      end
%The rest of the code updates the x and y coordinates
end

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Answer 1

Walter Roberson 2017-5-3

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Your line

current_t=temp_hourly(t,:); % this updates the value every iteration

gives the impression that current_t will be a vector. If so then

prob_thermoreg= current_t-threshold_t; % determines the probability

would be a vector. Then when you did

if prob_thermoreg>rn;

with it being a vector that test would be the equivalent of

if all(prob_thermoreg>rn)

which would fail if any member of prob_thermoreg was less than the random number.

Could you confirm whether current_t will be a vector or a scalar?

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Stephanie Diaz 2017-5-5

在 MATLAB Online 中打开

Hi Walter,

I'm not sure if this will be of much help, but below is the entire relevant code. Xpos and ypos are both initialized at 100. I think I understand what you're saying, but the probabilities are almost always greater than rn, which means maxy_tree and maxx_tree should update, correct?

       clear all
          close all
          A=dlmread('treecover_layer2.txt'); %tree cover map 
          B=dlmread('water_clip.txt'); %euclidean distance to water
          C=dlmread('evi_wet_l5.txt');%EVI wet season
          temp=dlmread('temp.txt'); %hourly temperature for 5 days in wet season
          temp_hourly=temp(:,2);%reads in only the column for temperature in the file (having 120 rows)
          threshold_t=30;
          xpos = 100;  % x-coordinate of initial position 
          ypos = 100;   % y-coordinate of initial position 
          maxtime = 120;  % number of time steps (24 hours times 5 days)
          range = 10;  % visual range 
          for i=1:maxtime  % iteration over time steps to the maximum 120 time steps
          % starting from xstart = xpos-range and ystart = ypos-range
              xstart = xpos-range; 
              ystart = ypos-range; 
              for t=1:120; %iteration over all t values 1-120 (5 days)
          current_t=temp_hourly(t,:); % updates current_t every iteration
          prob_thermoreg=1/(1+exp(-.05*(current_t-threshold_t))); % determmines probability given current_t
          rn=rand; %random number generator
          if prob_thermoreg>rn;
                    % The logic below will find the cell with the max value from the starting positions, xpos, ypos.
          maxtreecover = 0.0;  %find max larger than this
          maxx_tree = xstart;
          maxy_tree = ystart; 
          for jj=1:20  %double the radius 
          for ii=1:20  
                  if A(ystart + ii,xstart + jj) > maxtreecover; % if the value of A at different ii and jj is greater than max tree cover 
                      maxtreecover = A(ystart + ii,xstart + jj); %selection of the cell with max value
                      maxx_tree = xstart + jj;
                      maxy_tree = ystart + ii;
                  end
          end
          end
           end
              end
          newmaxtreecover = maxtreecover;  % This is cell selected
          newposx =  maxx_tree;  % This is the new x-coordinate 
          newposy =  maxy_tree;  % This is the new y-coordinate 
          xpossav(i) = xpos;  % save values of x-coordinate
          ypossav(i) = ypos;  % save values of y-coordinate
          timesav(i) = i;
          xpos = newposx % Update x-coordinate
          ypos = newposy % Update y-coordinate
          end
          image(A,'CDataMapping','scaled')
          figure %5
          plot(timesav,xpossav,timesav,ypossav), xlabel ('Time'), ylabel ('X, Y'), title ('')
          figure %5
      plot(xpossav,ypossav), xlabel ('X'), ylabel ('Y'), title ('')

Walter Roberson 2017-5-5

I do not see a vertical line as such. I see that most of the change in x and y occurs in the first step, and the rest in the second step, and then no change in x or y. Look at diff(xpossav) and diff(ypossav)

If you put in a disp() or fprintf() after the rand() you will see that the random test is satisfied on most (but not all) t values for every i.

If you look at your code, in each step you are looking for the highest point in A within a certain distance of the current point, and you move there, staying where you are if you are already at the highest point in that range. Then in the next iteration you repeat searching the same distance from where you are currently. Consider now what happens when you reach the highest point in that distance: there is no way to move off of it. So you go to the local peak and you get stuck there.

And that's what you are seeing: you move from the starting point, and you quickly get stuck at a local maxima. (You might even have gotten stuck at the global maxima.)

Stephanie Diaz 2017-5-5

I see exactly what you are saying, thank you! I will add some sort of if statement to prevent this, perhaps increasing the distance for selecting the maximum point.

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