I’m running Matlab 2023b on Ubuntu.
I’m just curious what this process is that’s been put in .config/autostart//mathworks-service-host.desktop to start at login?
Matlab starts fine without it but when I close Matlab, a process namber MathworksServiceHost keeps running.
It’s not a nice idea of having matlab-related processes running on the system after the application has been shut down. I have not noticed it on other version of Matlab. At least you should notify the user that a process is added to the autostart folder, and what it does.I’m running Matlab 2023b on Ubuntu.
I’m just curious what this process is that’s been put in .config/autostart//mathworks-service-host.desktop to start at login?
Matlab starts fine without it but when I close Matlab, a process namber MathworksServiceHost keeps running.
It’s not a nice idea of having matlab-related processes running on the system after the application has been shut down. I have not noticed it on other version of Matlab. At least you should notify the user that a process is added to the autostart folder, and what it does. I’m running Matlab 2023b on Ubuntu.
I’m just curious what this process is that’s been put in .config/autostart//mathworks-service-host.desktop to start at login?
Matlab starts fine without it but when I close Matlab, a process namber MathworksServiceHost keeps running.
It’s not a nice idea of having matlab-related processes running on the system after the application has been shut down. I have not noticed it on other version of Matlab. At least you should notify the user that a process is added to the autostart folder, and what it does. autostart, mathworksservicehost MATLAB Answers — New Questions

​

Hi all, I have some data to be fitted with the function (please refer to my code). However, despite manually setting the maximumfunctionevaluation limit, the computer doesn’t seem to take it and it says the solver stops prematurely. May I ask what have I done wrong?
%% Preparation
clear;clc

data = importdata("FCPIB-293K-2.5mW-400nm-Jan072021 -ibg -bg -chirp.csv"); % insert file path within parenthesis

%% Preamble

% Fundamental constants
h = 4.0135667696*10^-15; % units: eV/ Hz
c = 3*10^8; % SI units
kB = 8.617333268*10^-5; % units: eV/ K

% Clean up of data to select range of values
wavelength = data(1:end, 1);
delay_t = data(1, 1:end); % conatains all of the delay times
E = (h*c)./(wavelength*10^-9); % contains all of the probe energies
Range_E = E>=1.5 & E<=2.2;
Range_T = delay_t>=0.5 & delay_t<=1000;

% for one delay time
T = find(Range_T);
T_min = min(T);
T_max = max(T);
t = 57; % choose an integer b/w T_min and T_max
delaytime = delay_t(1, t);
disp(delaytime)

% Initial parameter guess and bounds
lb = [0, 293, -1]; ub = [Inf, 1200, 1];
y0 = [2*10^9, 1000, 0.5];

% Data for fitting
E_p = E(Range_E); % selected probe energies
delta_Abs = -1*data(Range_E,t);
delta_Abs_norm = delta_Abs./max(abs(delta_Abs)); % normalised delta_Abs
Range_Efit = E_p>=1.62 & E_p<=max(E_p);
E_fit = E_p(Range_Efit);
delta_Abs_norm_fit = delta_Abs_norm(Range_Efit);

% Fitting function
function F = MB(y, E_fit)
F = y(1).*exp(-(E_fit./(8.617333268*10^-5.*y(2)))) + y(3);
end

%% Curve fitting options

% % Initial parameter guess and bounds
% lb = [0, 293, -1]; ub = [Inf, 800, 1];
% y0 = [1.2*10^9, 700, 0.5];

% lsqcurvefit and choose between different algorithm that lsqcurvefit employs (3C1, comment those lines that are not choosen and uncomment the line that is choosen, if not, matlab will take the last line of "optim_lsq" by default)
optim_lsq = optimoptions(‘lsqcurvefit’, ‘Algorithm’, ‘levenberg-marquardt’, ‘MaxFunctionEvaluations’,10^10, ‘MaxIterations’, 10^10, ‘FunctionTolerance’,10^-10, ‘StepTolerance’, 10^-10);
% optim_lsq = optimoptions(‘lsqcurvefit’, ‘Algorithm’, ‘trust-region-reflective’, ‘MaxFunctionEvaluations’,10^10, ‘MaxIterations’,10^10, ‘FunctionTolerance’,10^-20, ‘StepTolerance’, 10^-20);
% optim_lsq = optimoptions(‘lsqcurvefit’, ‘Algorithm’, ‘interior-point’, ‘MaxFunctionEvaluations’,1000, ‘MaxIterations’, 1000, ‘FunctionTolerance’,10^-20, ‘StepTolerance’, 10^-20);

% Solver for lsqcurvefit
[y, residualnorm, residual, exitflag, output, lambda, jacobian] = lsqcurvefit(@MB, y0, E_fit, delta_Abs_norm_fit, lb, ub);

%% Plot command

plot(E_p, delta_Abs_norm,’Black’)
hold on
plot(E_fit, MB(y, E_fit), ‘LineWidth’, 1.0, ‘Color’, ‘red’)
xlabel(‘Probe Photon Energy (eV)’)
ylabel(‘Normalised Delta A (a.u.)’)
legend(‘Experimental Data’, ‘Fitted Curve’)
disp(y(1,1))
disp(y(1,2))
disp(y(1,3))Hi all, I have some data to be fitted with the function (please refer to my code). However, despite manually setting the maximumfunctionevaluation limit, the computer doesn’t seem to take it and it says the solver stops prematurely. May I ask what have I done wrong?
%% Preparation
clear;clc

data = importdata("FCPIB-293K-2.5mW-400nm-Jan072021 -ibg -bg -chirp.csv"); % insert file path within parenthesis

%% Preamble

% Fundamental constants
h = 4.0135667696*10^-15; % units: eV/ Hz
c = 3*10^8; % SI units
kB = 8.617333268*10^-5; % units: eV/ K

% Clean up of data to select range of values
wavelength = data(1:end, 1);
delay_t = data(1, 1:end); % conatains all of the delay times
E = (h*c)./(wavelength*10^-9); % contains all of the probe energies
Range_E = E>=1.5 & E<=2.2;
Range_T = delay_t>=0.5 & delay_t<=1000;

% for one delay time
T = find(Range_T);
T_min = min(T);
T_max = max(T);
t = 57; % choose an integer b/w T_min and T_max
delaytime = delay_t(1, t);
disp(delaytime)

% Initial parameter guess and bounds
lb = [0, 293, -1]; ub = [Inf, 1200, 1];
y0 = [2*10^9, 1000, 0.5];

% Data for fitting
E_p = E(Range_E); % selected probe energies
delta_Abs = -1*data(Range_E,t);
delta_Abs_norm = delta_Abs./max(abs(delta_Abs)); % normalised delta_Abs
Range_Efit = E_p>=1.62 & E_p<=max(E_p);
E_fit = E_p(Range_Efit);
delta_Abs_norm_fit = delta_Abs_norm(Range_Efit);

% Fitting function
function F = MB(y, E_fit)
F = y(1).*exp(-(E_fit./(8.617333268*10^-5.*y(2)))) + y(3);
end

%% Curve fitting options

% % Initial parameter guess and bounds
% lb = [0, 293, -1]; ub = [Inf, 800, 1];
% y0 = [1.2*10^9, 700, 0.5];

% lsqcurvefit and choose between different algorithm that lsqcurvefit employs (3C1, comment those lines that are not choosen and uncomment the line that is choosen, if not, matlab will take the last line of "optim_lsq" by default)
optim_lsq = optimoptions(‘lsqcurvefit’, ‘Algorithm’, ‘levenberg-marquardt’, ‘MaxFunctionEvaluations’,10^10, ‘MaxIterations’, 10^10, ‘FunctionTolerance’,10^-10, ‘StepTolerance’, 10^-10);
% optim_lsq = optimoptions(‘lsqcurvefit’, ‘Algorithm’, ‘trust-region-reflective’, ‘MaxFunctionEvaluations’,10^10, ‘MaxIterations’,10^10, ‘FunctionTolerance’,10^-20, ‘StepTolerance’, 10^-20);
% optim_lsq = optimoptions(‘lsqcurvefit’, ‘Algorithm’, ‘interior-point’, ‘MaxFunctionEvaluations’,1000, ‘MaxIterations’, 1000, ‘FunctionTolerance’,10^-20, ‘StepTolerance’, 10^-20);

% Solver for lsqcurvefit
[y, residualnorm, residual, exitflag, output, lambda, jacobian] = lsqcurvefit(@MB, y0, E_fit, delta_Abs_norm_fit, lb, ub);

%% Plot command

plot(E_p, delta_Abs_norm,’Black’)
hold on
plot(E_fit, MB(y, E_fit), ‘LineWidth’, 1.0, ‘Color’, ‘red’)
xlabel(‘Probe Photon Energy (eV)’)
ylabel(‘Normalised Delta A (a.u.)’)
legend(‘Experimental Data’, ‘Fitted Curve’)
disp(y(1,1))
disp(y(1,2))
disp(y(1,3)) Hi all, I have some data to be fitted with the function (please refer to my code). However, despite manually setting the maximumfunctionevaluation limit, the computer doesn’t seem to take it and it says the solver stops prematurely. May I ask what have I done wrong?
%% Preparation
clear;clc

data = importdata("FCPIB-293K-2.5mW-400nm-Jan072021 -ibg -bg -chirp.csv"); % insert file path within parenthesis

%% Preamble

% Fundamental constants
h = 4.0135667696*10^-15; % units: eV/ Hz
c = 3*10^8; % SI units
kB = 8.617333268*10^-5; % units: eV/ K

% Clean up of data to select range of values
wavelength = data(1:end, 1);
delay_t = data(1, 1:end); % conatains all of the delay times
E = (h*c)./(wavelength*10^-9); % contains all of the probe energies
Range_E = E>=1.5 & E<=2.2;
Range_T = delay_t>=0.5 & delay_t<=1000;

% for one delay time
T = find(Range_T);
T_min = min(T);
T_max = max(T);
t = 57; % choose an integer b/w T_min and T_max
delaytime = delay_t(1, t);
disp(delaytime)

% Initial parameter guess and bounds
lb = [0, 293, -1]; ub = [Inf, 1200, 1];
y0 = [2*10^9, 1000, 0.5];

% Data for fitting
E_p = E(Range_E); % selected probe energies
delta_Abs = -1*data(Range_E,t);
delta_Abs_norm = delta_Abs./max(abs(delta_Abs)); % normalised delta_Abs
Range_Efit = E_p>=1.62 & E_p<=max(E_p);
E_fit = E_p(Range_Efit);
delta_Abs_norm_fit = delta_Abs_norm(Range_Efit);

% Fitting function
function F = MB(y, E_fit)
F = y(1).*exp(-(E_fit./(8.617333268*10^-5.*y(2)))) + y(3);
end

%% Curve fitting options

% % Initial parameter guess and bounds
% lb = [0, 293, -1]; ub = [Inf, 800, 1];
% y0 = [1.2*10^9, 700, 0.5];

% lsqcurvefit and choose between different algorithm that lsqcurvefit employs (3C1, comment those lines that are not choosen and uncomment the line that is choosen, if not, matlab will take the last line of "optim_lsq" by default)
optim_lsq = optimoptions(‘lsqcurvefit’, ‘Algorithm’, ‘levenberg-marquardt’, ‘MaxFunctionEvaluations’,10^10, ‘MaxIterations’, 10^10, ‘FunctionTolerance’,10^-10, ‘StepTolerance’, 10^-10);
% optim_lsq = optimoptions(‘lsqcurvefit’, ‘Algorithm’, ‘trust-region-reflective’, ‘MaxFunctionEvaluations’,10^10, ‘MaxIterations’,10^10, ‘FunctionTolerance’,10^-20, ‘StepTolerance’, 10^-20);
% optim_lsq = optimoptions(‘lsqcurvefit’, ‘Algorithm’, ‘interior-point’, ‘MaxFunctionEvaluations’,1000, ‘MaxIterations’, 1000, ‘FunctionTolerance’,10^-20, ‘StepTolerance’, 10^-20);

% Solver for lsqcurvefit
[y, residualnorm, residual, exitflag, output, lambda, jacobian] = lsqcurvefit(@MB, y0, E_fit, delta_Abs_norm_fit, lb, ub);

%% Plot command

plot(E_p, delta_Abs_norm,’Black’)
hold on
plot(E_fit, MB(y, E_fit), ‘LineWidth’, 1.0, ‘Color’, ‘red’)
xlabel(‘Probe Photon Energy (eV)’)
ylabel(‘Normalised Delta A (a.u.)’)
legend(‘Experimental Data’, ‘Fitted Curve’)
disp(y(1,1))
disp(y(1,2))
disp(y(1,3)) curve fitting, lsqcurvefit MATLAB Answers — New Questions

​

A 4×14 matrix (C) is multiplied by each column of a 14xN matrix (x) – hence by N individual 14 element column vectors – to form N individual 4 element column vectors – represented by a 4xN matrix (y) -, where N is a known yet large number, let’s assume N = 132 for simplicity.
I use a for loop for this operation:
N = 132;
C = [0,1,0,0,0,0,0,0,0,-1,0,-0.68,0, 1.53;
0,0,0,1,0,0,0,0,0,-1,0,-0.64,0,-1.92;
0,0,0,0,0,1,0,0,0,-1,0, 0.86,0,-1.92;
0,0,0,0,0,0,0,1,0,-1,0, 0.91,0, 1.53];
x = rand(14,N);
for n = 1:N
y(:,n) = C*x(:,n);
end
y
This works fine, however, I wondered how this operation could be implemented without a for loop in MATLAB – all variables in the loop are available prior to the first iteration – to utilize MATLAB’s matrix multiplication optimization and thus improve runtime performance, or is this just not possible?
Thanks in advance for any help!A 4×14 matrix (C) is multiplied by each column of a 14xN matrix (x) – hence by N individual 14 element column vectors – to form N individual 4 element column vectors – represented by a 4xN matrix (y) -, where N is a known yet large number, let’s assume N = 132 for simplicity.
I use a for loop for this operation:
N = 132;
C = [0,1,0,0,0,0,0,0,0,-1,0,-0.68,0, 1.53;
0,0,0,1,0,0,0,0,0,-1,0,-0.64,0,-1.92;
0,0,0,0,0,1,0,0,0,-1,0, 0.86,0,-1.92;
0,0,0,0,0,0,0,1,0,-1,0, 0.91,0, 1.53];
x = rand(14,N);
for n = 1:N
y(:,n) = C*x(:,n);
end
y
This works fine, however, I wondered how this operation could be implemented without a for loop in MATLAB – all variables in the loop are available prior to the first iteration – to utilize MATLAB’s matrix multiplication optimization and thus improve runtime performance, or is this just not possible?
Thanks in advance for any help! A 4×14 matrix (C) is multiplied by each column of a 14xN matrix (x) – hence by N individual 14 element column vectors – to form N individual 4 element column vectors – represented by a 4xN matrix (y) -, where N is a known yet large number, let’s assume N = 132 for simplicity.
I use a for loop for this operation:
N = 132;
C = [0,1,0,0,0,0,0,0,0,-1,0,-0.68,0, 1.53;
0,0,0,1,0,0,0,0,0,-1,0,-0.64,0,-1.92;
0,0,0,0,0,1,0,0,0,-1,0, 0.86,0,-1.92;
0,0,0,0,0,0,0,1,0,-1,0, 0.91,0, 1.53];
x = rand(14,N);
for n = 1:N
y(:,n) = C*x(:,n);
end
y
This works fine, however, I wondered how this operation could be implemented without a for loop in MATLAB – all variables in the loop are available prior to the first iteration – to utilize MATLAB’s matrix multiplication optimization and thus improve runtime performance, or is this just not possible?
Thanks in advance for any help! matlab, matrix, for loop, matlab function, time series, speed MATLAB Answers — New Questions

​

Hey,
I am new to the Matlab Control System Toolbox and want to try out the Control System Tuner but I am facing a weird problem.
This is my control loop:

And I want to tune the PI controller to achieve a stable response. So I have specified the following Step Tracking Goal:
However, the Control System Tuner just gives me the maximum possible gain:

Does someone of you has an idea if I have to adjust the settings somehow or what else could be the reason for this behaviour?
ThanksHey,
I am new to the Matlab Control System Toolbox and want to try out the Control System Tuner but I am facing a weird problem.
This is my control loop:

And I want to tune the PI controller to achieve a stable response. So I have specified the following Step Tracking Goal:
However, the Control System Tuner just gives me the maximum possible gain:

Does someone of you has an idea if I have to adjust the settings somehow or what else could be the reason for this behaviour?
Thanks Hey,
I am new to the Matlab Control System Toolbox and want to try out the Control System Tuner but I am facing a weird problem.
This is my control loop:

And I want to tune the PI controller to achieve a stable response. So I have specified the following Step Tracking Goal:
However, the Control System Tuner just gives me the maximum possible gain:

Does someone of you has an idea if I have to adjust the settings somehow or what else could be the reason for this behaviour?
Thanks simulink, control MATLAB Answers — New Questions

​

Hi, I get the following error with the given code,

"Operands to the logical AND (&&) and OR (||) operators must be convertible to logical scalar values. Use the ANY or ALL functions to reduce operands to logical scalar values."

This performs a minimization using the active set method. But seemingly, it stops over this operator problem.

Any ideas welcome!

% Define symbolic variables
syms x1 x2 x3 lambda1 lambda3

% Objective function
f = x1^2 + x2^2 + x3^2 – x1 + 2*x2 – 4*x3;

% Constraints
g1 = -x1 + x2 + 1; % -x1 + x2 >= -1 is equivalent to g1 <= 0
g2 = x1 + x2 + x3 + 3; % x1 + x2 + x3 >= -3 is equivalent to g2 <= 0
g3 = x3; % x3 >= 0 is equivalent to g3 <= 0

% Initial point
x0 = [0; 0; 0];

% Iterative process
x = x0;
activeSet = []; % Initially empty active set

maxIter = 10; % Maximum number of iterations
tol = 1e-6; % Tolerance for convergence

for iter = 1:maxIter
% Compute gradients of the objective function and constraints
grad_f = gradient(f, [x1, x2, x3]);
grad_g1 = gradient(g1, [x1, x2, x3]);
grad_g2 = gradient(g2, [x1, x2, x3]);
grad_g3 = gradient(g3, [x1, x2, x3]);

% Evaluate gradients at the current point
grad_f_val = double(subs(grad_f, {x1, x2, x3}, x’));
grad_g1_val = double(subs(grad_g1, {x1, x2, x3}, x’));
grad_g2_val = double(subs(grad_g2, {x1, x2, x3}, x’));
grad_g3_val = double(subs(grad_g3, {x1, x2, x3}, x’));

% Check KKT conditions to determine active set
if abs(grad_g1_val) < tol && subs(g1, {x1, x2, x3}, x’) <= 0
activeSet = [activeSet, 1]; % Constraint 1 is active
end

if abs(grad_g2_val) < tol && subs(g2, {x1, x2, x3}, x’) <= 0
activeSet = [activeSet, 2]; % Constraint 2 is active
end

if abs(grad_g3_val) < tol && subs(g3, {x1, x2, x3}, x’) <= 0
activeSet = [activeSet, 3]; % Constraint 3 is active
end

% Solve the subproblem using the active set
A_eq = [];
b_eq = [];
A_ineq = [];
b_ineq = [];
lb = [];
ub = [];
options = optimoptions(‘quadprog’, ‘Display’, ‘off’);

if any(activeSet == 1)
A_ineq = [A_ineq; -1, 1, 0];
b_ineq = [b_ineq; -1];
end

if any(activeSet == 2)
A_ineq = [A_ineq; 1, 1, 1];
b_ineq = [b_ineq; -3];
end

if any(activeSet == 3)
A_ineq = [A_ineq; 0, 0, 1];
b_ineq = [b_ineq; 0];
end

[x_new, ~, exitflag] = quadprog(eye(3), -grad_f_val’, A_ineq, b_ineq, A_eq, b_eq, lb, ub, [], options);

% Check convergence
if norm(x_new – x) < tol
break;
end

% Update x and active set
x = x_new;
activeSet = unique(activeSet);
end

% Display results
disp([‘Optimal point: x = [‘, num2str(x’), ‘]’]);
disp([‘Objective function value: ‘, num2str(double(subs(f, {x1, x2, x3}, x’)))]);Hi, I get the following error with the given code,

"Operands to the logical AND (&&) and OR (||) operators must be convertible to logical scalar values. Use the ANY or ALL functions to reduce operands to logical scalar values."

This performs a minimization using the active set method. But seemingly, it stops over this operator problem.

Any ideas welcome!

% Define symbolic variables
syms x1 x2 x3 lambda1 lambda3

% Objective function
f = x1^2 + x2^2 + x3^2 – x1 + 2*x2 – 4*x3;

% Constraints
g1 = -x1 + x2 + 1; % -x1 + x2 >= -1 is equivalent to g1 <= 0
g2 = x1 + x2 + x3 + 3; % x1 + x2 + x3 >= -3 is equivalent to g2 <= 0
g3 = x3; % x3 >= 0 is equivalent to g3 <= 0

% Initial point
x0 = [0; 0; 0];

% Iterative process
x = x0;
activeSet = []; % Initially empty active set

maxIter = 10; % Maximum number of iterations
tol = 1e-6; % Tolerance for convergence

for iter = 1:maxIter
% Compute gradients of the objective function and constraints
grad_f = gradient(f, [x1, x2, x3]);
grad_g1 = gradient(g1, [x1, x2, x3]);
grad_g2 = gradient(g2, [x1, x2, x3]);
grad_g3 = gradient(g3, [x1, x2, x3]);

% Evaluate gradients at the current point
grad_f_val = double(subs(grad_f, {x1, x2, x3}, x’));
grad_g1_val = double(subs(grad_g1, {x1, x2, x3}, x’));
grad_g2_val = double(subs(grad_g2, {x1, x2, x3}, x’));
grad_g3_val = double(subs(grad_g3, {x1, x2, x3}, x’));

% Check KKT conditions to determine active set
if abs(grad_g1_val) < tol && subs(g1, {x1, x2, x3}, x’) <= 0
activeSet = [activeSet, 1]; % Constraint 1 is active
end

if abs(grad_g2_val) < tol && subs(g2, {x1, x2, x3}, x’) <= 0
activeSet = [activeSet, 2]; % Constraint 2 is active
end

if abs(grad_g3_val) < tol && subs(g3, {x1, x2, x3}, x’) <= 0
activeSet = [activeSet, 3]; % Constraint 3 is active
end

% Solve the subproblem using the active set
A_eq = [];
b_eq = [];
A_ineq = [];
b_ineq = [];
lb = [];
ub = [];
options = optimoptions(‘quadprog’, ‘Display’, ‘off’);

if any(activeSet == 1)
A_ineq = [A_ineq; -1, 1, 0];
b_ineq = [b_ineq; -1];
end

if any(activeSet == 2)
A_ineq = [A_ineq; 1, 1, 1];
b_ineq = [b_ineq; -3];
end

if any(activeSet == 3)
A_ineq = [A_ineq; 0, 0, 1];
b_ineq = [b_ineq; 0];
end

[x_new, ~, exitflag] = quadprog(eye(3), -grad_f_val’, A_ineq, b_ineq, A_eq, b_eq, lb, ub, [], options);

% Check convergence
if norm(x_new – x) < tol
break;
end

% Update x and active set
x = x_new;
activeSet = unique(activeSet);
end

% Display results
disp([‘Optimal point: x = [‘, num2str(x’), ‘]’]);
disp([‘Objective function value: ‘, num2str(double(subs(f, {x1, x2, x3}, x’)))]); Hi, I get the following error with the given code,

"Operands to the logical AND (&&) and OR (||) operators must be convertible to logical scalar values. Use the ANY or ALL functions to reduce operands to logical scalar values."

This performs a minimization using the active set method. But seemingly, it stops over this operator problem.

Any ideas welcome!

% Define symbolic variables
syms x1 x2 x3 lambda1 lambda3

% Objective function
f = x1^2 + x2^2 + x3^2 – x1 + 2*x2 – 4*x3;

% Constraints
g1 = -x1 + x2 + 1; % -x1 + x2 >= -1 is equivalent to g1 <= 0
g2 = x1 + x2 + x3 + 3; % x1 + x2 + x3 >= -3 is equivalent to g2 <= 0
g3 = x3; % x3 >= 0 is equivalent to g3 <= 0

% Initial point
x0 = [0; 0; 0];

% Iterative process
x = x0;
activeSet = []; % Initially empty active set

maxIter = 10; % Maximum number of iterations
tol = 1e-6; % Tolerance for convergence

for iter = 1:maxIter
% Compute gradients of the objective function and constraints
grad_f = gradient(f, [x1, x2, x3]);
grad_g1 = gradient(g1, [x1, x2, x3]);
grad_g2 = gradient(g2, [x1, x2, x3]);
grad_g3 = gradient(g3, [x1, x2, x3]);

% Evaluate gradients at the current point
grad_f_val = double(subs(grad_f, {x1, x2, x3}, x’));
grad_g1_val = double(subs(grad_g1, {x1, x2, x3}, x’));
grad_g2_val = double(subs(grad_g2, {x1, x2, x3}, x’));
grad_g3_val = double(subs(grad_g3, {x1, x2, x3}, x’));

% Check KKT conditions to determine active set
if abs(grad_g1_val) < tol && subs(g1, {x1, x2, x3}, x’) <= 0
activeSet = [activeSet, 1]; % Constraint 1 is active
end

if abs(grad_g2_val) < tol && subs(g2, {x1, x2, x3}, x’) <= 0
activeSet = [activeSet, 2]; % Constraint 2 is active
end

if abs(grad_g3_val) < tol && subs(g3, {x1, x2, x3}, x’) <= 0
activeSet = [activeSet, 3]; % Constraint 3 is active
end

% Solve the subproblem using the active set
A_eq = [];
b_eq = [];
A_ineq = [];
b_ineq = [];
lb = [];
ub = [];
options = optimoptions(‘quadprog’, ‘Display’, ‘off’);

if any(activeSet == 1)
A_ineq = [A_ineq; -1, 1, 0];
b_ineq = [b_ineq; -1];
end

if any(activeSet == 2)
A_ineq = [A_ineq; 1, 1, 1];
b_ineq = [b_ineq; -3];
end

if any(activeSet == 3)
A_ineq = [A_ineq; 0, 0, 1];
b_ineq = [b_ineq; 0];
end

[x_new, ~, exitflag] = quadprog(eye(3), -grad_f_val’, A_ineq, b_ineq, A_eq, b_eq, lb, ub, [], options);

% Check convergence
if norm(x_new – x) < tol
break;
end

% Update x and active set
x = x_new;
activeSet = unique(activeSet);
end

% Display results
disp([‘Optimal point: x = [‘, num2str(x’), ‘]’]);
disp([‘Objective function value: ‘, num2str(double(subs(f, {x1, x2, x3}, x’)))]); operands, scalar, values MATLAB Answers — New Questions

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I am doing a long calculations and they keep being interrupted constantly at random (as i assume) places. When re-running the code to save the ""corrupted" file once again, it without any problem. then, the problem repeats itself further down the file numbers. Due to the fact that the file is saved after re-running of the code, i assume it wasn’t corrupted in the first place. So i don’t really know what exactly the problem is. Would appreciate some help or suggestions. thanks!I am doing a long calculations and they keep being interrupted constantly at random (as i assume) places. When re-running the code to save the ""corrupted" file once again, it without any problem. then, the problem repeats itself further down the file numbers. Due to the fact that the file is saved after re-running of the code, i assume it wasn’t corrupted in the first place. So i don’t really know what exactly the problem is. Would appreciate some help or suggestions. thanks! I am doing a long calculations and they keep being interrupted constantly at random (as i assume) places. When re-running the code to save the ""corrupted" file once again, it without any problem. then, the problem repeats itself further down the file numbers. Due to the fact that the file is saved after re-running of the code, i assume it wasn’t corrupted in the first place. So i don’t really know what exactly the problem is. Would appreciate some help or suggestions. thanks! corrupted file, matlab, database MATLAB Answers — New Questions

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Hi, I am having a problem while I use the genetic algorithm. When I use the ga with only 3 populations it works, but when I increase the populations it gives me an error that a value must be a scalar.
I diden’t understand why he gives the error only when I increase the population fron 3 onwards. Maybe someone knows the problem and could help me?Hi, I am having a problem while I use the genetic algorithm. When I use the ga with only 3 populations it works, but when I increase the populations it gives me an error that a value must be a scalar.
I diden’t understand why he gives the error only when I increase the population fron 3 onwards. Maybe someone knows the problem and could help me? Hi, I am having a problem while I use the genetic algorithm. When I use the ga with only 3 populations it works, but when I increase the populations it gives me an error that a value must be a scalar.
I diden’t understand why he gives the error only when I increase the population fron 3 onwards. Maybe someone knows the problem and could help me? matlab, error, function, optimization, genetic algorithm MATLAB Answers — New Questions

​

Hi All,
I am using MATLAB 2023b trial version and can not work with NETCDF files.
In this case I am not able to simply read one netcdf file. What is going on?
Did I miss any matlab installation file? Is it a bug version? See below
the error I get:

>> test
Error using mexcdf
## Unrecognized Matlab version.
Error in ncread (line 46)
[ncid]=mexcdf(‘ncopen’,fname,’nc_nowrite’);
Error in netcdf_load (line 15)
val = ncread(ncfile,varname);
Error in test (line 3)
netcdf_load(‘swa12_2_grd.nc’);
>>
Thanks for any help,

LucianoHi All,
I am using MATLAB 2023b trial version and can not work with NETCDF files.
In this case I am not able to simply read one netcdf file. What is going on?
Did I miss any matlab installation file? Is it a bug version? See below
the error I get:

>> test
Error using mexcdf
## Unrecognized Matlab version.
Error in ncread (line 46)
[ncid]=mexcdf(‘ncopen’,fname,’nc_nowrite’);
Error in netcdf_load (line 15)
val = ncread(ncfile,varname);
Error in test (line 3)
netcdf_load(‘swa12_2_grd.nc’);
>>
Thanks for any help,

Luciano Hi All,
I am using MATLAB 2023b trial version and can not work with NETCDF files.
In this case I am not able to simply read one netcdf file. What is going on?
Did I miss any matlab installation file? Is it a bug version? See below
the error I get:

>> test
Error using mexcdf
## Unrecognized Matlab version.
Error in ncread (line 46)
[ncid]=mexcdf(‘ncopen’,fname,’nc_nowrite’);
Error in netcdf_load (line 15)
val = ncread(ncfile,varname);
Error in test (line 3)
netcdf_load(‘swa12_2_grd.nc’);
>>
Thanks for any help,

Luciano netcdf, matlab 2023b MATLAB Answers — New Questions

​

I dont understand why it stops after the first iteration and gives this error:
"Index exceeds the number of array elements. Index must not exceed 1"
g=9.8
nu= 10^-6 ;
c=1/2 ;
var_Y=0.1;
I_Y= 2.8;
s= 5;
C_beta=zeros(s)
C_Y=zeros(s)
S=0:1:4
for i=1:s
C_Y= (var_Y^2)*exp(abs(-S(i)./I_Y))
C_beta= (1/ (exp(c*var_y^2)))* ( ( exp(0.5*c*(c+1)*((var_y)^2) ) -1 )^2- c*(c+1) *(exp(0.5*c*(c+1)*(var_y)^2)-1)*(exp(var_y^2)-1)+(c^2)*(exp(C_Y(i))-1) )
plot (S,C_beta)
endI dont understand why it stops after the first iteration and gives this error:
"Index exceeds the number of array elements. Index must not exceed 1"
g=9.8
nu= 10^-6 ;
c=1/2 ;
var_Y=0.1;
I_Y= 2.8;
s= 5;
C_beta=zeros(s)
C_Y=zeros(s)
S=0:1:4
for i=1:s
C_Y= (var_Y^2)*exp(abs(-S(i)./I_Y))
C_beta= (1/ (exp(c*var_y^2)))* ( ( exp(0.5*c*(c+1)*((var_y)^2) ) -1 )^2- c*(c+1) *(exp(0.5*c*(c+1)*(var_y)^2)-1)*(exp(var_y^2)-1)+(c^2)*(exp(C_Y(i))-1) )
plot (S,C_beta)
end I dont understand why it stops after the first iteration and gives this error:
"Index exceeds the number of array elements. Index must not exceed 1"
g=9.8
nu= 10^-6 ;
c=1/2 ;
var_Y=0.1;
I_Y= 2.8;
s= 5;
C_beta=zeros(s)
C_Y=zeros(s)
S=0:1:4
for i=1:s
C_Y= (var_Y^2)*exp(abs(-S(i)./I_Y))
C_beta= (1/ (exp(c*var_y^2)))* ( ( exp(0.5*c*(c+1)*((var_y)^2) ) -1 )^2- c*(c+1) *(exp(0.5*c*(c+1)*(var_y)^2)-1)*(exp(var_y^2)-1)+(c^2)*(exp(C_Y(i))-1) )
plot (S,C_beta)
end for loop, index exceeds MATLAB Answers — New Questions

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I am creating an exercise for a course with a Live Script in Matlab 2016a.

I made some PNG drawings with free body diagrams. Unfortunately when they are inserted the Live Script, the image quality is dramatically decreased, making the text in the images very difficult to read.
I tried also TIFF and JPEG with the same results.

Is there a way to include an image in a Live Script with the original quality and resolution?

Where can I suggest the addition of support for SVG or some format that support vector images?

Thank you.I am creating an exercise for a course with a Live Script in Matlab 2016a.

I made some PNG drawings with free body diagrams. Unfortunately when they are inserted the Live Script, the image quality is dramatically decreased, making the text in the images very difficult to read.
I tried also TIFF and JPEG with the same results.

Is there a way to include an image in a Live Script with the original quality and resolution?

Where can I suggest the addition of support for SVG or some format that support vector images?

Thank you. I am creating an exercise for a course with a Live Script in Matlab 2016a.

I made some PNG drawings with free body diagrams. Unfortunately when they are inserted the Live Script, the image quality is dramatically decreased, making the text in the images very difficult to read.
I tried also TIFF and JPEG with the same results.

Is there a way to include an image in a Live Script with the original quality and resolution?

Where can I suggest the addition of support for SVG or some format that support vector images?

Thank you. live script, livescript MATLAB Answers — New Questions

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