How to remove for loops in this code?

Question

Prativa sahoo 2016-10-14

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评论： Prativa sahoo 2016-10-17

Hi, I am new to matlab. i am running the following code .It is taking a very long time to process. Can anyone suggest how to rewrite it to reduce the computation time. arr1 = 4d array with size (512 512 122 4)

parfor n=1:slice
  n    
 for i=1:width
    for j=1:height
      options = optimset('Algorithm', 'levenberg-marquardt', 'display','off');
      warning('off');            
        St = squeeze(arr1(i,j,n,:));
        if St(1)>50
            St = St./St(1);
            St = St(:)';
            bat = 1;
            c_bat = St(1);
            %pl_parm=[TTP,slop1,slop2];
            pl_parm=[2;0;.1];
            xdata = [1:length(St)];
            lb = [2;0;-1];
            ub = [4;10;1];
              [par_PL,resnorm,residual,exitflag,output,lambda,jacobian] = lsqcurvefit(@PLmodel,pl_parm,xdata,St,lb,ub,options);
              TTP(i,j,n)=par_PL(1);
              Slope1(i,j,n)=par_PL(2);
              Slope2(i,j,n)=par_PL(3);
          end
      end
   end
end

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Answer 1

Marc Jakobi 2016-10-14

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在 MATLAB Online 中打开

If lsqcurvefit() can't be run on matrices, you may not be able to reduce the loop nesting. But if it is a lot of data, you can decrease time by a bit by taking variables that don't change out of the loop. Setting them every time is not efficient. Also, try to avoid displaying things (like n) in the command window. Command window outputs significantly increase the time it takes to perform computations.

options = optimset('Algorithm', 'levenberg-marquardt', 'display','off');
warning('off');  
bat = 1;
%pl_parm=[TTP,slop1,slop2];
pl_parm=[2;0;.1];
lb = [2;0;-1];
ub = [4;10;1];
  parfor n=1:slice 
   for i=1:width
      for j=1:height    
          St = squeeze(arr1(i,j,n,:));
          if St(1)>50
              St = St./St(1);
              St = St(:)';
              c_bat = St(1);
              xdata = [1:length(St)];
                [par_PL,resnorm,residual,exitflag,output,lambda,jacobian] = lsqcurvefit(@PLmodel,pl_parm,xdata,St,lb,ub,options);
                TTP(i,j,n)=par_PL(1);
                Slope1(i,j,n)=par_PL(2);
                Slope2(i,j,n)=par_PL(3);
            end
        end
     end
  end

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Answer 2

Walter Roberson 2016-10-14

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https://ww2.mathworks.cn/matlabcentral/answers/307359-how-to-remove-for-loops-in-this-code#answer_239058

lsqcurvefit is not itself vectorizable.

You have bounds constraints, so lsqcurvefit is going to turn this into a lsqnonlin call with trust-region-reflective selected.

You could pull out all the hyperpages where arr1(:,:,:,1) > 50, and arrange those as a series of rows or columns in a 2D array. The question then becomes whether there is a way that you could ask to perform the fitting over the entire 2D array at once. I would have to think more about whether there would be a practical way to transform a least-squared model to have one more dimension; it is not obvious to me that it is possible in general. However, if we had the code for your PLmodel and we could see what it is you are fitting, we just might be able to think of a different approach.

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Walter Roberson 2016-10-15

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Vectorize that function to improve performance.

function [fx] = PLmodel(parm,X)
    C=1;
    BAT=1;
    TTP = parm(1);
    slop1 = parm(2);
    slop2 = parm(3);
    fx = zeros(size(X));
    mask = X < BAT;
    fx(mask) = C;
    mask = BAT <= X & X < TTP;
    fx(mask) = C + slop1 * (X(mask) - BAT);
    mask = X >= TTP;
    fx(mask) = C + slop1 * (TTP-BAT) + slop2 * (X(mask) - TTP);