Failure in initial objective function evaluation. LSQCURVEFIT cannot continue.

Question

Thaer Ismail 2020-1-6

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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/499075-failure-in-initial-objective-function-evaluation-lsqcurvefit-cannot-continue

评论： Walter Roberson 2020-2-27

raw = xlsread('File', 2); % read in sheet number 2
Pc = raw(60:141, 1); 
Sw = raw(60:141, 9); 
plot(Sw,Pc,'ro')
 F = @(x,xdata)1-x(1)*exp(-(x(2)/xdata)^(x(3)));
x0 = [3 6 0.6];
[x,resnorm,~,exitflag,output] = lsqcurvefit(F,x0,Sw,Pc)

I keep getting this error.

Error in Skelt_LS_Code (line 16)

[x,resnorm,~,exitflag,output] = lsqcurvefit(F,x0,Sw,Pc)

Caused by:

Failure in initial objective function evaluation. LSQCURVEFIT cannot continue.

Any help is appreciated. Thank you

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Answer 1

Walter Roberson 2020-1-6

1
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/499075-failure-in-initial-objective-function-evaluation-lsqcurvefit-cannot-continue#answer_408843

在 MATLAB Online 中打开

F = @(x,xdata)1-x(1)*exp(-(x(2)./xdata).^(x(3)));

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Thaer Ismail 2020-1-6

在 MATLAB Online 中打开

bad skelt.JPG

Thank you, now I am having a diferent proplem. The least suares always does one iteration for me. , I changed the initial guess multiple times but even if the numbers of Iterations increase a little I always get a very bad match with my data, See attached . What am I doing wrong?

get in this in command window

Test

Local minimum found.

Optimization completed because the size of the gradient is less than

the value of the optimality tolerance.

<stopping criteria details>
x =
    1.5098    7.0574    9.4972
resnorm =
   1.2341e+06
exitflag =
     1
output = 
  struct with fields:
    firstorderopt: 0
       iterations: 1
        funcCount: 8
     cgiterations: 0
        algorithm: 'trust-region-reflective'
         stepsize: 10
          message: '↵Local minimum found.↵↵Optimization completed because the size of the gradient is less than↵the value of the optimality tolerance.↵↵<stopping criteria details>↵↵Optimization completed: The first-order optimality measure, 0.000000e+00,↵is less than options.OptimalityTolerance = 1.000000e-06.↵↵'

>>

Thi Na Le 2020-2-27

ydata in previous reply was wrong. this is modification:

a0=4;

xdata=...

[5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100 105 110 115 120 125 130 135 140 145 150 155 160 165 170 175 180];

ydata=...

[0.04178 0.081 0.09475 0.1157 0.1326 0.1468 0.1587 0.169 0.178 0.186 0.193 0.199 0.205 0.211 0.215 0.22 0.224 0.229 0.233 0.238 0.242 0.245 0.248 0.251 0.254 0.257 0.258 0.261 0.264 0.266 0.269 0.272 0.274 0.277 0.273 0.275];

fun=@(x,xdata)a0*(1+((4.5*x(1)*x(2)*xdata)/(5.5+x(2)*xdata)));

x0=[0.01 0.0001];

>> plot(xdata,ydata,'o')

>> x = lsqcurvefit(fun,x0,xdata,ydata)

Error using lsqcurvefit (line 262)

Function value and YDATA sizes are not equal.