In the ribbon command, the ribbons run along each column of the matrix. The Y vector must be of length = to the number of rows in the matrix. How do I get the ribbons to run along each row of the matrix? I tried many combinations of flipud, fliplr, transpose, etc., and either the axis is going in the wrong direction, or the labels are wrong.
Z=[0,1,2,2; 1,2,3,3; 2,3,4,4; 3,4,5,5]
Y=[0;1;2;3]
ribbon(Y,Z,0.1);
Here the ribbons run in the y direction, but I want them to run in the x direction. Nothing else, e.g., the axis numbering, should change.In the ribbon command, the ribbons run along each column of the matrix. The Y vector must be of length = to the number of rows in the matrix. How do I get the ribbons to run along each row of the matrix? I tried many combinations of flipud, fliplr, transpose, etc., and either the axis is going in the wrong direction, or the labels are wrong.
Z=[0,1,2,2; 1,2,3,3; 2,3,4,4; 3,4,5,5]
Y=[0;1;2;3]
ribbon(Y,Z,0.1);
Here the ribbons run in the y direction, but I want them to run in the x direction. Nothing else, e.g., the axis numbering, should change. In the ribbon command, the ribbons run along each column of the matrix. The Y vector must be of length = to the number of rows in the matrix. How do I get the ribbons to run along each row of the matrix? I tried many combinations of flipud, fliplr, transpose, etc., and either the axis is going in the wrong direction, or the labels are wrong.
Z=[0,1,2,2; 1,2,3,3; 2,3,4,4; 3,4,5,5]
Y=[0;1;2;3]
ribbon(Y,Z,0.1);
Here the ribbons run in the y direction, but I want them to run in the x direction. Nothing else, e.g., the axis numbering, should change. ribbon plot orientation MATLAB Answers — New Questions

​

Hi,
I’m solving a nonlinear system of equations with lsqnonlin and want to save the evolution of values of X.
The ouput of the system is defined by a function file ‘error.m’, which takes X with size 4×1 and returns a vector of residuals with size 8×1.
I run a script with the structure below that sets the some fixed parameters for error.m, then calls the lsqnonlin solver and error.m for n cases.
clear all,clc,close all
load measure;

%initialization: set some constant inputs for ‘error.m’ and options for the
%solver

% solve nCases
for i=1:nCases
inputs.measured=measure(i);
X=lsqnonlin(@(x)error(inputs,x),x0,lb,ub,options)
save X X;
end

I want to store the values of X over the iterations, not only the solution. There are these examples in Optimization Solver Output Functions, but they use nested functions and I don’t know how to adapt them to my script structure.
function stop = myoutput(x,optimvalues,state);
stop = false;
if isequal(state,’iter’)
history = [history; x];
end
end
How will the output function ‘myoutput’ access the variable X inside the lsqnonlin?
I’ve tried to write the myoutput at the end of the main script, predefined history = [ ] in the for loop i=1:nCases and set options = optimset(‘OutputFcn’, @myoutput);
However, the function ‘myoutput’ doesn’t find th ehistory variable to append. Why is that happening?Hi,
I’m solving a nonlinear system of equations with lsqnonlin and want to save the evolution of values of X.
The ouput of the system is defined by a function file ‘error.m’, which takes X with size 4×1 and returns a vector of residuals with size 8×1.
I run a script with the structure below that sets the some fixed parameters for error.m, then calls the lsqnonlin solver and error.m for n cases.
clear all,clc,close all
load measure;

%initialization: set some constant inputs for ‘error.m’ and options for the
%solver

% solve nCases
for i=1:nCases
inputs.measured=measure(i);
X=lsqnonlin(@(x)error(inputs,x),x0,lb,ub,options)
save X X;
end

I want to store the values of X over the iterations, not only the solution. There are these examples in Optimization Solver Output Functions, but they use nested functions and I don’t know how to adapt them to my script structure.
function stop = myoutput(x,optimvalues,state);
stop = false;
if isequal(state,’iter’)
history = [history; x];
end
end
How will the output function ‘myoutput’ access the variable X inside the lsqnonlin?
I’ve tried to write the myoutput at the end of the main script, predefined history = [ ] in the for loop i=1:nCases and set options = optimset(‘OutputFcn’, @myoutput);
However, the function ‘myoutput’ doesn’t find th ehistory variable to append. Why is that happening? Hi,
I’m solving a nonlinear system of equations with lsqnonlin and want to save the evolution of values of X.
The ouput of the system is defined by a function file ‘error.m’, which takes X with size 4×1 and returns a vector of residuals with size 8×1.
I run a script with the structure below that sets the some fixed parameters for error.m, then calls the lsqnonlin solver and error.m for n cases.
clear all,clc,close all
load measure;

%initialization: set some constant inputs for ‘error.m’ and options for the
%solver

% solve nCases
for i=1:nCases
inputs.measured=measure(i);
X=lsqnonlin(@(x)error(inputs,x),x0,lb,ub,options)
save X X;
end

I want to store the values of X over the iterations, not only the solution. There are these examples in Optimization Solver Output Functions, but they use nested functions and I don’t know how to adapt them to my script structure.
function stop = myoutput(x,optimvalues,state);
stop = false;
if isequal(state,’iter’)
history = [history; x];
end
end
How will the output function ‘myoutput’ access the variable X inside the lsqnonlin?
I’ve tried to write the myoutput at the end of the main script, predefined history = [ ] in the for loop i=1:nCases and set options = optimset(‘OutputFcn’, @myoutput);
However, the function ‘myoutput’ doesn’t find th ehistory variable to append. Why is that happening? lsqnonlin, output, iteration, optimization MATLAB Answers — New Questions

​

hello
I have a neural network structure of my data and I want to do a multiobjective optimization for example with NSGA-II. How could I connect my ANN to NSGA-II?
I tried the next code:
[x_ga1,fval_ga1,~,gaoutput1] = gamultiobj(fun,nvar,A,b,Aeq,beq,lb,ub,opts_ga);
where "fun" is my ANN function. but It makes an error!!hello
I have a neural network structure of my data and I want to do a multiobjective optimization for example with NSGA-II. How could I connect my ANN to NSGA-II?
I tried the next code:
[x_ga1,fval_ga1,~,gaoutput1] = gamultiobj(fun,nvar,A,b,Aeq,beq,lb,ub,opts_ga);
where "fun" is my ANN function. but It makes an error!! hello
I have a neural network structure of my data and I want to do a multiobjective optimization for example with NSGA-II. How could I connect my ANN to NSGA-II?
I tried the next code:
[x_ga1,fval_ga1,~,gaoutput1] = gamultiobj(fun,nvar,A,b,Aeq,beq,lb,ub,opts_ga);
where "fun" is my ANN function. but It makes an error!! ann, nsga-ii, multiobjective optimization MATLAB Answers — New Questions

​

I want to define a StepTolerance for the lsqnonlin with ‘trust-region-reflective’algorithm to solve a system of 4 variables, so X has dimension 4×1.
The documention Tolerance Details says that this algorithm uses a Absolute Step Tolerance.
In Tolerances and Stopping Criteria I found this:
"StepTolerance is a lower bound on the size of a step, meaning the norm of (xi – xi+1). If the solver attempts to take a step that is smaller than StepTolerance, the iterations end."
Is this norm the same of function norm, the Euclidean norm?I want to define a StepTolerance for the lsqnonlin with ‘trust-region-reflective’algorithm to solve a system of 4 variables, so X has dimension 4×1.
The documention Tolerance Details says that this algorithm uses a Absolute Step Tolerance.
In Tolerances and Stopping Criteria I found this:
"StepTolerance is a lower bound on the size of a step, meaning the norm of (xi – xi+1). If the solver attempts to take a step that is smaller than StepTolerance, the iterations end."
Is this norm the same of function norm, the Euclidean norm? I want to define a StepTolerance for the lsqnonlin with ‘trust-region-reflective’algorithm to solve a system of 4 variables, so X has dimension 4×1.
The documention Tolerance Details says that this algorithm uses a Absolute Step Tolerance.
In Tolerances and Stopping Criteria I found this:
"StepTolerance is a lower bound on the size of a step, meaning the norm of (xi – xi+1). If the solver attempts to take a step that is smaller than StepTolerance, the iterations end."
Is this norm the same of function norm, the Euclidean norm? lsqnonlin, tolerances, norm MATLAB Answers — New Questions

​

I have a 1×1 struct variable that contains 6 fields. Each field is a 1×1 CompactClassificationNeuralNetwork, results from a neural network I use to train on images for image segmentation. When I open this struct in MATLAB R2021a, the struct contains all 6 fields. When I open it in 2024a, the struct contains 6 empty fields. The data doesn’t appear. I have had trouble finding answers online. What might be the issue here?I have a 1×1 struct variable that contains 6 fields. Each field is a 1×1 CompactClassificationNeuralNetwork, results from a neural network I use to train on images for image segmentation. When I open this struct in MATLAB R2021a, the struct contains all 6 fields. When I open it in 2024a, the struct contains 6 empty fields. The data doesn’t appear. I have had trouble finding answers online. What might be the issue here? I have a 1×1 struct variable that contains 6 fields. Each field is a 1×1 CompactClassificationNeuralNetwork, results from a neural network I use to train on images for image segmentation. When I open this struct in MATLAB R2021a, the struct contains all 6 fields. When I open it in 2024a, the struct contains 6 empty fields. The data doesn’t appear. I have had trouble finding answers online. What might be the issue here? neural network, image segmentation MATLAB Answers — New Questions

​

I am trying to create a Method of characteristics Code from JD Andersons book "Modern Compressible Flow with Historical Perspective" using example 11.1. Error arises when I try to obtain the coordinates of the points 2-7; where 7 is the n_div which I have taken.
Code:
clear;
clc;
close all;
%% Initial parameters %%
radian_to_deg = 180/pi;
degree_to_radian = pi/180;
prompt = "Enter a Mach Number ranging from 1.5 to 4: ";
Me = input(prompt);
prompt_1 = "Enter the number of divisions: ";
n_div = input(prompt_1);
%prompt_2 = "Enter the throat radius: ";
%TR = input(prompt_2);
g = 1.4;
mach_angle= [];
theta = [];
theta_a = [];
y=[];
x=[];
v=[];
v_a=[];
dydx_minus = [];
dydx_plus = [];
new_Mach=[];
%% get mach angle
ma_f = @(x) (asind(1/x)) ;
%% get theta_max
A = sqrt((g+1)/(g-1));
B = (g-1)/(g+1);
pm_f = @(x) (A*atand(sqrt(B*(x^2-1))) – atand(sqrt(x^2-1)));
theta_max = pm_f(Me)/2;
%% extraction of fractional part of theta_max
theta_i = sign(theta_max)*(abs(theta_max) – floor(abs(theta_max)));
%% Storing different values of theta_a
for i = 1:n_div
theta_a(i,1) = theta_i ;
theta_i = theta_i + 3.0;
end
v_a = theta_a;
%% Getting properties of a-1 characteristic line
ya=1;
xa=0;
%theta_a(1,1) = theta_i(1,1);
v_a(1,1) = theta_a(1,1);
%point 1
y(1,1) = 0;
Km_1 = theta_a(1,1) + v_a(1,1);
theta(1,1)= 0.5*(Km_1);
v(1,1) = 0.5*(Km_1);
%% get mach number for v(1,1)
syms x
f = @(x) (A*atand(sqrt(B*(x^2-1))) – atand(sqrt(x^2-1))-v(1,1));
f1 = matlabFunction(diff(f(x)));
%NR Method using a while loop
change = 10;
Mguess = 1.1;
while (change>1e-6)
Mnew = Mguess – f(Mguess)/f1(Mguess);
change = abs(Mguess – Mnew);
Mguess = Mnew;
end
new_Mach(1,1) = Mnew;
mach_angle(1,1) = ma_f(Mnew);
x(1,1) = -ya/tand(theta(1,1)-mach_angle(1,1));
%% rest of points:
for i = 2:n_div
Km = (theta_a(i,1)) + (v_a(i,1));
Kp = theta(i-1,1) – v(i-1,1);
theta(i,1) = 0.5*(Km+Kp);
v(i,1) = 0.5*(Km-Kp);

end
%% Calculating the Unknown Mach Number and corresponding Mach Angle using NR Method
syms x
for i=2:n_div
f = @(x) (A*atand(sqrt(B*(x^2-1))) – atand(sqrt(x^2-1))-v(i,1));
f1 = matlabFunction(diff(f(x)));
Mguess = 1.1;
change = 10;
while (change>1e-6)
Mnew = Mguess – f(Mguess)/f1(Mguess);
change = abs(Mguess – Mnew);
Mguess = Mnew;
end
new_Mach(i,1) = Mnew;
mach_angle(i,1) = ma_f(Mnew);
end

%% slopes and locations of points from 2-7
for i=2:n_div
dydx_minus(i,1) = tand(0.5*(theta(i)+theta(i)) – 0.5*(mach_angle(i)+mach_angle(i)));
dydx_plus(i,1) = tand(0.5*(theta(i) + theta(i-1))) + (0.5*(mach_angle(i) + mach_angle(i-1)));
x(i,1) = (y(i-1,1) – ya – (dydx_plus(i,1)*x(i-1)))/(dydx_minus(i,1) – dydx_plus(i,1));
y(i,1) = (dydx_plus(i,1)*(x(i,1)-x(i-1))) + y(i-1);
end
%slope and location of wall point 8
slopew1_minus = tand(theta_max);
slopew1_plus = dydx_plus(end,1);
xw = (y(end,1)-ya-(slopew1_plus*x(end,1)))/(slopew1_minus – slopew1_plus);
yw = (slopew1_plus*(xw(1,1)-x(end,1)))+y(end,1);
Error:
Error in MOC_prac (line 111)
y(i,1) = (dydx_plus(i,1)*(a_double(i,1)-a_double(i-1))) + y(i-1);

Unable to perform assignment because value of type ‘sym’ is not convertible to ‘double’.

Error in MOC_prac (line 111)
y(i,1) = (dydx_plus(i,1)*(x(i,1)-x(i-1))) + y(i-1);

Caused by:
Error using mupadengine/feval2char
Unable to convert expression containing symbolic variables into double array. Apply ‘subs’ function
first to substitute values for variables.
Is there any way I can resolve this error? Thank you!I am trying to create a Method of characteristics Code from JD Andersons book "Modern Compressible Flow with Historical Perspective" using example 11.1. Error arises when I try to obtain the coordinates of the points 2-7; where 7 is the n_div which I have taken.
Code:
clear;
clc;
close all;
%% Initial parameters %%
radian_to_deg = 180/pi;
degree_to_radian = pi/180;
prompt = "Enter a Mach Number ranging from 1.5 to 4: ";
Me = input(prompt);
prompt_1 = "Enter the number of divisions: ";
n_div = input(prompt_1);
%prompt_2 = "Enter the throat radius: ";
%TR = input(prompt_2);
g = 1.4;
mach_angle= [];
theta = [];
theta_a = [];
y=[];
x=[];
v=[];
v_a=[];
dydx_minus = [];
dydx_plus = [];
new_Mach=[];
%% get mach angle
ma_f = @(x) (asind(1/x)) ;
%% get theta_max
A = sqrt((g+1)/(g-1));
B = (g-1)/(g+1);
pm_f = @(x) (A*atand(sqrt(B*(x^2-1))) – atand(sqrt(x^2-1)));
theta_max = pm_f(Me)/2;
%% extraction of fractional part of theta_max
theta_i = sign(theta_max)*(abs(theta_max) – floor(abs(theta_max)));
%% Storing different values of theta_a
for i = 1:n_div
theta_a(i,1) = theta_i ;
theta_i = theta_i + 3.0;
end
v_a = theta_a;
%% Getting properties of a-1 characteristic line
ya=1;
xa=0;
%theta_a(1,1) = theta_i(1,1);
v_a(1,1) = theta_a(1,1);
%point 1
y(1,1) = 0;
Km_1 = theta_a(1,1) + v_a(1,1);
theta(1,1)= 0.5*(Km_1);
v(1,1) = 0.5*(Km_1);
%% get mach number for v(1,1)
syms x
f = @(x) (A*atand(sqrt(B*(x^2-1))) – atand(sqrt(x^2-1))-v(1,1));
f1 = matlabFunction(diff(f(x)));
%NR Method using a while loop
change = 10;
Mguess = 1.1;
while (change>1e-6)
Mnew = Mguess – f(Mguess)/f1(Mguess);
change = abs(Mguess – Mnew);
Mguess = Mnew;
end
new_Mach(1,1) = Mnew;
mach_angle(1,1) = ma_f(Mnew);
x(1,1) = -ya/tand(theta(1,1)-mach_angle(1,1));
%% rest of points:
for i = 2:n_div
Km = (theta_a(i,1)) + (v_a(i,1));
Kp = theta(i-1,1) – v(i-1,1);
theta(i,1) = 0.5*(Km+Kp);
v(i,1) = 0.5*(Km-Kp);

end
%% Calculating the Unknown Mach Number and corresponding Mach Angle using NR Method
syms x
for i=2:n_div
f = @(x) (A*atand(sqrt(B*(x^2-1))) – atand(sqrt(x^2-1))-v(i,1));
f1 = matlabFunction(diff(f(x)));
Mguess = 1.1;
change = 10;
while (change>1e-6)
Mnew = Mguess – f(Mguess)/f1(Mguess);
change = abs(Mguess – Mnew);
Mguess = Mnew;
end
new_Mach(i,1) = Mnew;
mach_angle(i,1) = ma_f(Mnew);
end

%% slopes and locations of points from 2-7
for i=2:n_div
dydx_minus(i,1) = tand(0.5*(theta(i)+theta(i)) – 0.5*(mach_angle(i)+mach_angle(i)));
dydx_plus(i,1) = tand(0.5*(theta(i) + theta(i-1))) + (0.5*(mach_angle(i) + mach_angle(i-1)));
x(i,1) = (y(i-1,1) – ya – (dydx_plus(i,1)*x(i-1)))/(dydx_minus(i,1) – dydx_plus(i,1));
y(i,1) = (dydx_plus(i,1)*(x(i,1)-x(i-1))) + y(i-1);
end
%slope and location of wall point 8
slopew1_minus = tand(theta_max);
slopew1_plus = dydx_plus(end,1);
xw = (y(end,1)-ya-(slopew1_plus*x(end,1)))/(slopew1_minus – slopew1_plus);
yw = (slopew1_plus*(xw(1,1)-x(end,1)))+y(end,1);
Error:
Error in MOC_prac (line 111)
y(i,1) = (dydx_plus(i,1)*(a_double(i,1)-a_double(i-1))) + y(i-1);

Unable to perform assignment because value of type ‘sym’ is not convertible to ‘double’.

Error in MOC_prac (line 111)
y(i,1) = (dydx_plus(i,1)*(x(i,1)-x(i-1))) + y(i-1);

Caused by:
Error using mupadengine/feval2char
Unable to convert expression containing symbolic variables into double array. Apply ‘subs’ function
first to substitute values for variables.
Is there any way I can resolve this error? Thank you! I am trying to create a Method of characteristics Code from JD Andersons book "Modern Compressible Flow with Historical Perspective" using example 11.1. Error arises when I try to obtain the coordinates of the points 2-7; where 7 is the n_div which I have taken.
Code:
clear;
clc;
close all;
%% Initial parameters %%
radian_to_deg = 180/pi;
degree_to_radian = pi/180;
prompt = "Enter a Mach Number ranging from 1.5 to 4: ";
Me = input(prompt);
prompt_1 = "Enter the number of divisions: ";
n_div = input(prompt_1);
%prompt_2 = "Enter the throat radius: ";
%TR = input(prompt_2);
g = 1.4;
mach_angle= [];
theta = [];
theta_a = [];
y=[];
x=[];
v=[];
v_a=[];
dydx_minus = [];
dydx_plus = [];
new_Mach=[];
%% get mach angle
ma_f = @(x) (asind(1/x)) ;
%% get theta_max
A = sqrt((g+1)/(g-1));
B = (g-1)/(g+1);
pm_f = @(x) (A*atand(sqrt(B*(x^2-1))) – atand(sqrt(x^2-1)));
theta_max = pm_f(Me)/2;
%% extraction of fractional part of theta_max
theta_i = sign(theta_max)*(abs(theta_max) – floor(abs(theta_max)));
%% Storing different values of theta_a
for i = 1:n_div
theta_a(i,1) = theta_i ;
theta_i = theta_i + 3.0;
end
v_a = theta_a;
%% Getting properties of a-1 characteristic line
ya=1;
xa=0;
%theta_a(1,1) = theta_i(1,1);
v_a(1,1) = theta_a(1,1);
%point 1
y(1,1) = 0;
Km_1 = theta_a(1,1) + v_a(1,1);
theta(1,1)= 0.5*(Km_1);
v(1,1) = 0.5*(Km_1);
%% get mach number for v(1,1)
syms x
f = @(x) (A*atand(sqrt(B*(x^2-1))) – atand(sqrt(x^2-1))-v(1,1));
f1 = matlabFunction(diff(f(x)));
%NR Method using a while loop
change = 10;
Mguess = 1.1;
while (change>1e-6)
Mnew = Mguess – f(Mguess)/f1(Mguess);
change = abs(Mguess – Mnew);
Mguess = Mnew;
end
new_Mach(1,1) = Mnew;
mach_angle(1,1) = ma_f(Mnew);
x(1,1) = -ya/tand(theta(1,1)-mach_angle(1,1));
%% rest of points:
for i = 2:n_div
Km = (theta_a(i,1)) + (v_a(i,1));
Kp = theta(i-1,1) – v(i-1,1);
theta(i,1) = 0.5*(Km+Kp);
v(i,1) = 0.5*(Km-Kp);

end
%% Calculating the Unknown Mach Number and corresponding Mach Angle using NR Method
syms x
for i=2:n_div
f = @(x) (A*atand(sqrt(B*(x^2-1))) – atand(sqrt(x^2-1))-v(i,1));
f1 = matlabFunction(diff(f(x)));
Mguess = 1.1;
change = 10;
while (change>1e-6)
Mnew = Mguess – f(Mguess)/f1(Mguess);
change = abs(Mguess – Mnew);
Mguess = Mnew;
end
new_Mach(i,1) = Mnew;
mach_angle(i,1) = ma_f(Mnew);
end

%% slopes and locations of points from 2-7
for i=2:n_div
dydx_minus(i,1) = tand(0.5*(theta(i)+theta(i)) – 0.5*(mach_angle(i)+mach_angle(i)));
dydx_plus(i,1) = tand(0.5*(theta(i) + theta(i-1))) + (0.5*(mach_angle(i) + mach_angle(i-1)));
x(i,1) = (y(i-1,1) – ya – (dydx_plus(i,1)*x(i-1)))/(dydx_minus(i,1) – dydx_plus(i,1));
y(i,1) = (dydx_plus(i,1)*(x(i,1)-x(i-1))) + y(i-1);
end
%slope and location of wall point 8
slopew1_minus = tand(theta_max);
slopew1_plus = dydx_plus(end,1);
xw = (y(end,1)-ya-(slopew1_plus*x(end,1)))/(slopew1_minus – slopew1_plus);
yw = (slopew1_plus*(xw(1,1)-x(end,1)))+y(end,1);
Error:
Error in MOC_prac (line 111)
y(i,1) = (dydx_plus(i,1)*(a_double(i,1)-a_double(i-1))) + y(i-1);

Unable to perform assignment because value of type ‘sym’ is not convertible to ‘double’.

Error in MOC_prac (line 111)
y(i,1) = (dydx_plus(i,1)*(x(i,1)-x(i-1))) + y(i-1);

Caused by:
Error using mupadengine/feval2char
Unable to convert expression containing symbolic variables into double array. Apply ‘subs’ function
first to substitute values for variables.
Is there any way I can resolve this error? Thank you! #syms, #subs, #double MATLAB Answers — New Questions

​

Hello, all:
I try to create a FMU for Linux in windows system. but after I have met one error when I try to build. see following:

Failed to set up the docker environment for cross-platform compilation because the container could not be retrieved. If the computer does not have internet access, check documentation for manually downloading the docker container.
docker container failed to start

a few weeks ago, I alread successed creat a FMU for Linux in windows system. but I don’t know why this time when I try to build FMU again, one error happened?
can you help me to solve it?
thank you.Hello, all:
I try to create a FMU for Linux in windows system. but after I have met one error when I try to build. see following:

Failed to set up the docker environment for cross-platform compilation because the container could not be retrieved. If the computer does not have internet access, check documentation for manually downloading the docker container.
docker container failed to start

a few weeks ago, I alread successed creat a FMU for Linux in windows system. but I don’t know why this time when I try to build FMU again, one error happened?
can you help me to solve it?
thank you. Hello, all:
I try to create a FMU for Linux in windows system. but after I have met one error when I try to build. see following:

Failed to set up the docker environment for cross-platform compilation because the container could not be retrieved. If the computer does not have internet access, check documentation for manually downloading the docker container.
docker container failed to start

a few weeks ago, I alread successed creat a FMU for Linux in windows system. but I don’t know why this time when I try to build FMU again, one error happened?
can you help me to solve it?
thank you. fmu linux MATLAB Answers — New Questions

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Dear all,
I’m trying to remove the background (not perfectly black) from the attached image. I have tried many methods, including setting thresholds and visualizing the data with the attached code. However, I realized that this might not be the best approach for this image because it also removes information within the circle (tomography of a cylindrical sample). I believe the best way would be to define a mask with the radius of the circle, but I don’t know how to determine it. Can anyone help fix the issues in my code or define a new one for the circular mask? The final aim is to calculate the area of the cracks.

I really appreciate any help!

clear all
close all
clc
I= imread(‘image_1567.png’);
FG = fliplr(imadjust(I,[0.05 1]));
sout = size(I);
squaresize = [10 10];
xx = mod(0:(sout(2)-1),squaresize(2)*2)<squaresize(2);
yy = mod(0:(sout(1)-1),squaresize(1)*2)<squaresize(1);
BG = im2uint8(0.3 + bsxfun(@xor,xx,yy’)*0.4);
mask = FG>10;
outpict = BG;
outpict(mask) = FG(mask);
outpict = uint8(double(FG).*mask + double(BG).*(1-mask));
subplot(3,2,1);
imshow(I,[]);
title(‘Original Grayscale Image’, ‘FontSize’, 15);
subplot(3,2,2);
imhist(I);
title(‘Histogram of original image’);
subplot(3,2,3);
imhist(outpict);
[counts, grayLevels] = imhist(outpict);
bar(grayLevels, counts, ‘EdgeColor’, ‘r’, ‘FaceColor’, ‘b’, ‘BarWidth’, 1);
xlim([0, max(outpict(:))]);
title(‘Histogram of output image with threshold 60’);
subplot(3,2,4);
thresholdValue1 = 60;
f.InvertHardcopy = ‘off’;
binaryImage1 = outpict > thresholdValue1;
imshow(binaryImage1, []);
title(‘Binary Image threshold 60’);
f.InvertHardcopy = ‘off’;
figure (1)Dear all,
I’m trying to remove the background (not perfectly black) from the attached image. I have tried many methods, including setting thresholds and visualizing the data with the attached code. However, I realized that this might not be the best approach for this image because it also removes information within the circle (tomography of a cylindrical sample). I believe the best way would be to define a mask with the radius of the circle, but I don’t know how to determine it. Can anyone help fix the issues in my code or define a new one for the circular mask? The final aim is to calculate the area of the cracks.

I really appreciate any help!

clear all
close all
clc
I= imread(‘image_1567.png’);
FG = fliplr(imadjust(I,[0.05 1]));
sout = size(I);
squaresize = [10 10];
xx = mod(0:(sout(2)-1),squaresize(2)*2)<squaresize(2);
yy = mod(0:(sout(1)-1),squaresize(1)*2)<squaresize(1);
BG = im2uint8(0.3 + bsxfun(@xor,xx,yy’)*0.4);
mask = FG>10;
outpict = BG;
outpict(mask) = FG(mask);
outpict = uint8(double(FG).*mask + double(BG).*(1-mask));
subplot(3,2,1);
imshow(I,[]);
title(‘Original Grayscale Image’, ‘FontSize’, 15);
subplot(3,2,2);
imhist(I);
title(‘Histogram of original image’);
subplot(3,2,3);
imhist(outpict);
[counts, grayLevels] = imhist(outpict);
bar(grayLevels, counts, ‘EdgeColor’, ‘r’, ‘FaceColor’, ‘b’, ‘BarWidth’, 1);
xlim([0, max(outpict(:))]);
title(‘Histogram of output image with threshold 60’);
subplot(3,2,4);
thresholdValue1 = 60;
f.InvertHardcopy = ‘off’;
binaryImage1 = outpict > thresholdValue1;
imshow(binaryImage1, []);
title(‘Binary Image threshold 60’);
f.InvertHardcopy = ‘off’;
figure (1) Dear all,
I’m trying to remove the background (not perfectly black) from the attached image. I have tried many methods, including setting thresholds and visualizing the data with the attached code. However, I realized that this might not be the best approach for this image because it also removes information within the circle (tomography of a cylindrical sample). I believe the best way would be to define a mask with the radius of the circle, but I don’t know how to determine it. Can anyone help fix the issues in my code or define a new one for the circular mask? The final aim is to calculate the area of the cracks.

I really appreciate any help!

clear all
close all
clc
I= imread(‘image_1567.png’);
FG = fliplr(imadjust(I,[0.05 1]));
sout = size(I);
squaresize = [10 10];
xx = mod(0:(sout(2)-1),squaresize(2)*2)<squaresize(2);
yy = mod(0:(sout(1)-1),squaresize(1)*2)<squaresize(1);
BG = im2uint8(0.3 + bsxfun(@xor,xx,yy’)*0.4);
mask = FG>10;
outpict = BG;
outpict(mask) = FG(mask);
outpict = uint8(double(FG).*mask + double(BG).*(1-mask));
subplot(3,2,1);
imshow(I,[]);
title(‘Original Grayscale Image’, ‘FontSize’, 15);
subplot(3,2,2);
imhist(I);
title(‘Histogram of original image’);
subplot(3,2,3);
imhist(outpict);
[counts, grayLevels] = imhist(outpict);
bar(grayLevels, counts, ‘EdgeColor’, ‘r’, ‘FaceColor’, ‘b’, ‘BarWidth’, 1);
xlim([0, max(outpict(:))]);
title(‘Histogram of output image with threshold 60’);
subplot(3,2,4);
thresholdValue1 = 60;
f.InvertHardcopy = ‘off’;
binaryImage1 = outpict > thresholdValue1;
imshow(binaryImage1, []);
title(‘Binary Image threshold 60’);
f.InvertHardcopy = ‘off’;
figure (1) image segmentation, imshow, imhist, background, image analysis MATLAB Answers — New Questions

​

Hello,
I’m trying to train a PPO agent, but I’m encountering the following issue:
From a certain time, the agent don’t learn anymore (although the agent is only in a local maximum). Let’s say that for the ten first episodes the agent gets a very bad reward, since it’s actually perfoming bad. Then, on the 11th episode (see graph below), the agent found a local maxmimum by updating its actions value to 30 and -30 (these are the gains coefficients of a PI controller). Finally, starting from the 12th episode (i.e. the next one), the agent don’t update its action values anymore.
As a solution, I’ve already tried to increase the EntropyLossWeight, from 0.02 to 1. I’ve tried a lot of values in this range, and it seems like nothing is efficient.
Another parameter may influence the result: from different actions taken in a very wide range of values (e.g. from [1; ∞] for the first action) any system output is perceptible, and thus any variation in the reward can’t be seen watever the action value taken within this range of values. In another words, on the picture below, the agent tried three differents values of gains, but the three actions values produced the same result, So, maybe the agent can’t learn from it.
So, I would like it to continue exploring, although it just got a better reward, since it is still not the best it can achieve.

Link to PPO agent options, including EntropyLossWeight: Options for PPO agent – MATLAB – MathWorks Switzerland

Any help would be very kind!

Thanks a lot in advance!
NicolasHello,
I’m trying to train a PPO agent, but I’m encountering the following issue:
From a certain time, the agent don’t learn anymore (although the agent is only in a local maximum). Let’s say that for the ten first episodes the agent gets a very bad reward, since it’s actually perfoming bad. Then, on the 11th episode (see graph below), the agent found a local maxmimum by updating its actions value to 30 and -30 (these are the gains coefficients of a PI controller). Finally, starting from the 12th episode (i.e. the next one), the agent don’t update its action values anymore.
As a solution, I’ve already tried to increase the EntropyLossWeight, from 0.02 to 1. I’ve tried a lot of values in this range, and it seems like nothing is efficient.
Another parameter may influence the result: from different actions taken in a very wide range of values (e.g. from [1; ∞] for the first action) any system output is perceptible, and thus any variation in the reward can’t be seen watever the action value taken within this range of values. In another words, on the picture below, the agent tried three differents values of gains, but the three actions values produced the same result, So, maybe the agent can’t learn from it.
So, I would like it to continue exploring, although it just got a better reward, since it is still not the best it can achieve.

Link to PPO agent options, including EntropyLossWeight: Options for PPO agent – MATLAB – MathWorks Switzerland

Any help would be very kind!

Thanks a lot in advance!
Nicolas Hello,
I’m trying to train a PPO agent, but I’m encountering the following issue:
From a certain time, the agent don’t learn anymore (although the agent is only in a local maximum). Let’s say that for the ten first episodes the agent gets a very bad reward, since it’s actually perfoming bad. Then, on the 11th episode (see graph below), the agent found a local maxmimum by updating its actions value to 30 and -30 (these are the gains coefficients of a PI controller). Finally, starting from the 12th episode (i.e. the next one), the agent don’t update its action values anymore.
As a solution, I’ve already tried to increase the EntropyLossWeight, from 0.02 to 1. I’ve tried a lot of values in this range, and it seems like nothing is efficient.
Another parameter may influence the result: from different actions taken in a very wide range of values (e.g. from [1; ∞] for the first action) any system output is perceptible, and thus any variation in the reward can’t be seen watever the action value taken within this range of values. In another words, on the picture below, the agent tried three differents values of gains, but the three actions values produced the same result, So, maybe the agent can’t learn from it.
So, I would like it to continue exploring, although it just got a better reward, since it is still not the best it can achieve.

Link to PPO agent options, including EntropyLossWeight: Options for PPO agent – MATLAB – MathWorks Switzerland

Any help would be very kind!

Thanks a lot in advance!
Nicolas reinforcement learning, ppo, entropy loss weight, local maximum MATLAB Answers — New Questions

​

For instance, I have vector a = 1 2 3 4 5, or simply a=[1:5]. How can I write a ‘for’ loop that sums up all the elements while showing intermediate results? I want the last result to be 15, as in, 1+2+3+4+5. So far I’ve only managed to sum up elements like this: 1+2 = 3, 2+3 = 5 and so on. What I want is a ‘for’ loop that factors in the previous summation and sums it up with the next.
The code I’ve written so far is:

a= [1:5]
for i=1:5
c=sum(a(i)+a(i+1))

disp(c)
endFor instance, I have vector a = 1 2 3 4 5, or simply a=[1:5]. How can I write a ‘for’ loop that sums up all the elements while showing intermediate results? I want the last result to be 15, as in, 1+2+3+4+5. So far I’ve only managed to sum up elements like this: 1+2 = 3, 2+3 = 5 and so on. What I want is a ‘for’ loop that factors in the previous summation and sums it up with the next.
The code I’ve written so far is:

a= [1:5]
for i=1:5
c=sum(a(i)+a(i+1))

disp(c)
end For instance, I have vector a = 1 2 3 4 5, or simply a=[1:5]. How can I write a ‘for’ loop that sums up all the elements while showing intermediate results? I want the last result to be 15, as in, 1+2+3+4+5. So far I’ve only managed to sum up elements like this: 1+2 = 3, 2+3 = 5 and so on. What I want is a ‘for’ loop that factors in the previous summation and sums it up with the next.
The code I’ve written so far is:

a= [1:5]
for i=1:5
c=sum(a(i)+a(i+1))

disp(c)
end for loop MATLAB Answers — New Questions

​