I have a problem in performing a non linear fit with Gnu Octave. Basically I need to perform a global fit with some shared parameters, while keeping others fixed.
The following code works perfectly in Matlab, but Octave returns an error
error: operator *: nonconformant arguments (op1 is 34x1, op2 is 4x1)
Attached my code and the data to play with:
clear
close all
clc
pkg load optim
D = dlmread('hd', ';'); % raw data
bkg = D(1,2:end); % 4 sensors bkg
x = D(2:end,1); % input signal
Y = D(2:end,2:end); % 4 sensors reposnse
W = 1./Y; % weights
b0 = [7 .04 .01 .1 .5 2 1]; % educated guess for start the fit
%% model function
F = #(b) ((bkg + (b(1) - bkg).*(1-exp(-(b(2:5).*x).^b(6))).^b(7)) - Y) .* W;
opts = optimset("Display", "iter");
lb = [5 .001 .001 .001 .001 .01 1];
ub = [];
[b, resnorm, residual, exitflag, output, lambda, Jacob\] = ...
lsqnonlin(F,b0,lb,ub,opts)
To give more info, giving array b0, b0(1), b0(6) and b0(7) are shared among the 4 dataset, while b0(2:5) are peculiar of each dataset.
Thank you for your help and suggestions! ;)
Raw data:
0,0.3105,0.31342,0.31183,0.31117
0.013229,0.329,0.3295,0.332,0.372
0.013229,0.328,0.33,0.33,0.373
0.021324,0.33,0.3305,0.33633,0.399
0.021324,0.325,0.3265,0.333,0.397
0.037763,0.33,0.3255,0.34467,0.461
0.037763,0.327,0.3285,0.347,0.456
0.069405,0.338,0.3265,0.36533,0.587
0.069405,0.3395,0.329,0.36667,0.589
0.12991,0.357,0.3385,0.41333,0.831
0.12991,0.358,0.3385,0.41433,0.837
0.25368,0.393,0.347,0.501,1.302
0.25368,0.3915,0.3515,0.498,1.278
0.51227,0.458,0.3735,0.668,2.098
0.51227,0.47,0.3815,0.68467,2.124
1.0137,0.61,0.4175,1.008,3.357
1.0137,0.599,0.422,1,3.318
2.0162,0.89,0.5335,1.645,5.006
2.0162,0.872,0.5325,1.619,4.938
4.0192,1.411,0.716,2.674,6.595
4.0192,1.418,0.7205,2.691,6.766
8.0315,2.34,1.118,4.195,7.176
8.0315,2.33,1.126,4.161,6.74
16.04,3.759,1.751,5.9,7.174
16.04,3.762,1.748,5.911,7.151
32.102,5.418,2.942,7.164,7.149
32.102,5.406,2.941,7.164,7.175
64.142,7.016,4.478,7.174,7.176
64.142,7.018,4.402,7.175,7.175
128.32,7.176,6.078,7.175,7.176
128.32,7.175,6.107,7.175,7.173
255.72,7.165,7.162,7.165,7.165
255.72,7.165,7.164,7.166,7.166
511.71,7.165,7.165,7.165,7.165
511.71,7.165,7.165,7.166,7.164
Giving the function definition above, if you call it by F(b0) in the command windows, you will get a 34x4 matrix which is correct, since variable Y has the same size.
In that way I can (in theory) compute the standard formula for lsqnonlin (fit - measured)^2
I was trying to solve a system of non-linear equations and check the stability of its equilibrium points. Initially, I declared two equations
adot = -a + 2*a^3 + b
bdot = -a -b
By equating both the equations with 0, I get the equilibrium points. Now, I am trying to get the Jacobian of the [adot;bdot] matrix using the jacobian([adot;bdot],[a,b]) method of symbolic package in Octave, which should just return a matrix whose items are the partial derivatives of "adot" and "bdot" w.r.t. "a" and "b", but it gives the following error
error: subscript indices must be integers or boolean
Can anyone tell me where I'm going wrong with this?
Edit: I'm adding the complete code down below:
pkg load symbolic
syms x y
xdot = -x + 2*x^3 + y;
ydot = -x - y;
[xeq,yeq] = solve(xdot==0,ydot==0);
xeq = double(xeq);
yeq = double(yeq);
jacobian_matrix = jacobian([xdot;ydot]);
At this point I'm getting the above mentioned error. The values in the [xeq,yeq] matrix are the equilibrium points of the system, which are to be used later on.
So I am trying to solve this problem from coursera regarding onevsAll classification. It comes under the ml course under Andrew NG. I am not able to find mistake in my code and it keeps showing this error
error: fmincg: operator +: nonconformant arguments (op1 is 401x1, op2 is 4x1)
error: called from
fmincg at line 87 column 5
oneVsAll at line 60 column 13
ex3 at line 77 column 13
I have tried reading the fmincg code but I cannot understand the problem.
function [all_theta] = oneVsAll(X, y, num_labels, lambda)
% Some useful variables
m = size(X, 1);
n = size(X, 2);
% You need to return the following variables correctly
all_theta = zeros(num_labels, n + 1);
% Add ones to the X data matrix
X = [ones(m, 1) X];
for c = 1:num_labels
initial_theta = zeros(n+1,1) ;
options = optimset('GradObj', 'on', 'MaxIter', 50);
[theta] = fmincg (#(t)(lrCostFunction(t, X, (y == c), lambda)),initial_theta, options);
all_theta(c, :) = theta;
end;
Program is showing error mentioned above regarding the fmincg file.
I can't make matrices with variables in it for some reason. I get following message.
>>> A= [a b ;(-1-a) (1-b); (1+a) b]
error: horizontal dimensions mismatch (2x3 vs 1x1)
Why is it? Please show me correct way if I'm wrong.
In Matlab you first need to assign a variable before you can use it,
a = 1;
b = a+1;
This will thus give an error,
clear;
b = a+1; % ERROR! Undefined function or variable 'a
Matlab does never accept unassigned variables. This is because, on the lowest level, you do not have a. You will have machine code which is assgined the value of a. This is handled by the JIT compiler in Matlab, so you do not need to worry about this though.
If you want to use something as the variable which you have in maths you can specifically express this to matlab. The object is called a sym and the syntax that define the sym x to a variable xis,
syms x;
That said, you can define a vector or a matrix as,
syms a b x y; % Assign the syms
A = [x y]; % Vector
B = A= [a b ;(-1-a) (1-b); (1+a) b]; % Matrix.
The size of a matrix can be found with size(M) or for dim n size(M,n). You can calcuate the matrix product M3=M1*M2 if and only if M1 have the size m * n and M2 have the size n * p. The size of M3 will then be m * p. This will also mean that the operation A^N = A * A * ... is only allowed when m=n so to say, the matrix is square. This can be verified in matlab by the comparison,
syms a b
A = [a,1;56,b]
if size(A,1) == size(A,2)
disp(['A is a square matrix of size ', num2str(size(A,1)]);
else
disp('A is not square');
end
These are the basic rules for assigning variables in Matlab as well as for matrix multiplication. Further, a google search on the error error: 'x' undefined does only give me octave hits. Are you using octave? In that case I cannot guarantee that you can use sym objects or that the syntaxes are correct.
I am new to Octave although I can say I am an expert Matlab user. I am running Octave on a Linux server (Red Hat) remotely through PuTTY, from a windows machine.
I am observing a very strange behavior in Octave. I call myfun(a) which performs as expected giving the sought results. Now, if I run, say, myfun(b) with b!=a, I get again myfun(a). Clear -f does not solve the problem. I need to reboot octave to change the parameters.
What am I doing wrong?
Thanks a lot
Francesco
This is the code for the function I mentioned:
function [a, v, obj, infos, iter] = mle_garch( p )
#{
% this function estimates the GARCH(1,1) parameters
% it is assumed we pass the adjusted price level p
#}
global y = (diff(log(p))-mean(diff(log(p))))*100;
global h = zeros(size(y));
a0 = [var(y)*0.9; 0.8; 0.1];
[a, obj, infos, iter] = sqp(a0, #loglike_garch, [], #loglike_con, [], [], 1000);
v = sqrt(h * 260);
endfunction
function g = loglike_garch( a )
global y h
n = length(y);
h(1) = var(y);
for i = 2 : n,
h(i) = a(1) + a(2) * h(i-1) + a(3) * y(i-1)^2;
endfor
g = 0.5 * ( sum(log(h)) + sum(y.^2./h) ) / n;
endfunction
function f = loglike_con( a )
f = [1;0;0;0] + [0 -1 -1;eye(3)] * a;
endfunction
I'm assuming the myfun you mentioned is mle_garch. The problem is the way you're initializing the global h and v variables (do you really need them to be global?). When you have a piece of code like this
global y = (diff(log(p))-mean(diff(log(p))))*100;
global h = zeros(size(y));
the values of y and h are defined the first time only. You can change their values later on, but this specific lines will never be ran again. Since your code only uses the input argument to define these two variables, the value which you use to run the function the first time will be used every single other time. If you really want to keep those variables global, replace it with the following:
global y;
global h;
y = (diff(log(p))-mean(diff(log(p))))*100;
h = zeros(size(y));
But I don't see any reason to keep them global so just don't make them global.
Also, you mentioned this code worked fine in Matlab. I was under the impression that you couldn't initialize global and persistent variables in Matlab which would make your code illegal in Matlab.