Hello everyone.
I want to ask a question regarding my final year project.
I’m currently doing a prediction system using:
UCI heart disease dataset.
Ensemble method (Subspace Discriminant) trained model from Classifier Learner App.
a GUI from app designer.
The system shown no problem when detecting a high parameter for high risk patient data and correctly shows ‘Heart Disease Detected’ but for a low parameter for a normal patient data it still shows the output as ‘Heart Disease Detected’. It is because of the dataset’s value comes from patients that already suspect with heart disease or the model used is sensitive. The GUI screenshot is suppose to be a normal patient data.
If you have an insight about this please share with me. Thank you.
I’ll share the coding used in the app designer and the GUI with some of the patient attribute data where the target is suppose to be the outcome of this system prediction.
properties (Access = private)
modelData = load(‘HeartModel.mat’,’trainedModel’);
end

methods (Access = private)

function startupFcn(app)

% Set DropDown items and ItemsData for numerical values

% Sex
app.SexDropDown.Items = {‘Female’, ‘Male’};
app.SexDropDown.ItemsData = [0, 1];

% Chest Pain (cp)
app.ChestPainDropDown.Items = {‘Normal’,’Typical Angina’, ‘Atypical Angina’, ‘Non-anginal Pain’, ‘Asymptomatic’};
app.ChestPainDropDown.ItemsData = [0, 1, 2, 3, 4];

% Fasting Blood Sugar (fbs)
app.FastingBloodSugarDropDown.Items = {‘<= 120 mg/dL’, ‘> 120 mg/dL’};
app.FastingBloodSugarDropDown.ItemsData = [0, 1];

% Rest ECG (restecg)
app.RestECGDropDown.Items = {‘Normal’, ‘ST-T Wave Abnormality’, ‘LV Hypertrophy’};
app.RestECGDropDown.ItemsData = [0, 1, 2];

% Slope
app.SlopeDropDown.Items = {‘Upsloping’, ‘Flat’, ‘Downsloping’};
app.SlopeDropDown.ItemsData = [1, 2, 3];

% Exercise Angina (exang)
app.ExerciseAnginaDropDown.Items = {‘No’, ‘Yes’};
app.ExerciseAnginaDropDown.ItemsData = [0, 1];

% CA
app.CADropDown.Items = {‘0’, ‘1’, ‘2’, ‘3’};
app.CADropDown.ItemsData = [0, 1, 2, 3];

% Thal
app.ThalDropDown.Items = {‘Normal’, ‘Fixed Defect’, ‘Reversible Defect’};
app.ThalDropDown.ItemsData = [3, 6, 7];

end
end

% Button pushed function: PredictButton
function PredictButtonPushed(app, event)

% Collect all inputs (convert to double to be safe)
age = double(app.AgeEditField.Value);
sex = double(app.SexDropDown.Value);
cp = double(app.ChestPainDropDown.Value);
trestbps = double(app.RestingBPEditField.Value);
chol = double(app.CholesterolEditField.Value);
fbs = double(app.FastingBloodSugarDropDown.Value);
restecg = double(app.RestECGDropDown.Value);
thalach = double(app.MaxHeartRateEditField.Value);
exang = double(app.ExerciseAnginaDropDown.Value);
oldpeak = double(app.OldpeakEditField.Value);
slope = double(app.SlopeDropDown.Value);
ca = double(app.CADropDown.Value);
thal = double(app.ThalDropDown.Value);

% Create input table
T = table(age, sex, cp, trestbps, chol, fbs, restecg, thalach, …
exang, oldpeak, slope, ca, thal, …
‘VariableNames’, {‘age’,’sex’,’cp’,’trestbps’,’chol’,’fbs’,…
‘restecg’,’thalach’,’exang’,’oldpeak’,…
‘slope’,’ca’,’thal’});

%Prediction
label = app.modelData.trainedModel.predictFcn(T);

% Display result
if label == 0
app.ResultLabel.Text = ‘No Heart Disease’;
app.ResultLabel.FontColor = [0 1 0]; % Green
else
app.ResultLabel.Text = ‘Heart Disease Detected’;
app.ResultLabel.FontColor = [1 0 0]; % Red
endHello everyone.
I want to ask a question regarding my final year project.
I’m currently doing a prediction system using:
UCI heart disease dataset.
Ensemble method (Subspace Discriminant) trained model from Classifier Learner App.
a GUI from app designer.
The system shown no problem when detecting a high parameter for high risk patient data and correctly shows ‘Heart Disease Detected’ but for a low parameter for a normal patient data it still shows the output as ‘Heart Disease Detected’. It is because of the dataset’s value comes from patients that already suspect with heart disease or the model used is sensitive. The GUI screenshot is suppose to be a normal patient data.
If you have an insight about this please share with me. Thank you.
I’ll share the coding used in the app designer and the GUI with some of the patient attribute data where the target is suppose to be the outcome of this system prediction.
properties (Access = private)
modelData = load(‘HeartModel.mat’,’trainedModel’);
end

methods (Access = private)

function startupFcn(app)

% Set DropDown items and ItemsData for numerical values

% Sex
app.SexDropDown.Items = {‘Female’, ‘Male’};
app.SexDropDown.ItemsData = [0, 1];

% Chest Pain (cp)
app.ChestPainDropDown.Items = {‘Normal’,’Typical Angina’, ‘Atypical Angina’, ‘Non-anginal Pain’, ‘Asymptomatic’};
app.ChestPainDropDown.ItemsData = [0, 1, 2, 3, 4];

% Fasting Blood Sugar (fbs)
app.FastingBloodSugarDropDown.Items = {‘<= 120 mg/dL’, ‘> 120 mg/dL’};
app.FastingBloodSugarDropDown.ItemsData = [0, 1];

% Rest ECG (restecg)
app.RestECGDropDown.Items = {‘Normal’, ‘ST-T Wave Abnormality’, ‘LV Hypertrophy’};
app.RestECGDropDown.ItemsData = [0, 1, 2];

% Slope
app.SlopeDropDown.Items = {‘Upsloping’, ‘Flat’, ‘Downsloping’};
app.SlopeDropDown.ItemsData = [1, 2, 3];

% Exercise Angina (exang)
app.ExerciseAnginaDropDown.Items = {‘No’, ‘Yes’};
app.ExerciseAnginaDropDown.ItemsData = [0, 1];

% CA
app.CADropDown.Items = {‘0’, ‘1’, ‘2’, ‘3’};
app.CADropDown.ItemsData = [0, 1, 2, 3];

% Thal
app.ThalDropDown.Items = {‘Normal’, ‘Fixed Defect’, ‘Reversible Defect’};
app.ThalDropDown.ItemsData = [3, 6, 7];

end
end

% Button pushed function: PredictButton
function PredictButtonPushed(app, event)

% Collect all inputs (convert to double to be safe)
age = double(app.AgeEditField.Value);
sex = double(app.SexDropDown.Value);
cp = double(app.ChestPainDropDown.Value);
trestbps = double(app.RestingBPEditField.Value);
chol = double(app.CholesterolEditField.Value);
fbs = double(app.FastingBloodSugarDropDown.Value);
restecg = double(app.RestECGDropDown.Value);
thalach = double(app.MaxHeartRateEditField.Value);
exang = double(app.ExerciseAnginaDropDown.Value);
oldpeak = double(app.OldpeakEditField.Value);
slope = double(app.SlopeDropDown.Value);
ca = double(app.CADropDown.Value);
thal = double(app.ThalDropDown.Value);

% Create input table
T = table(age, sex, cp, trestbps, chol, fbs, restecg, thalach, …
exang, oldpeak, slope, ca, thal, …
‘VariableNames’, {‘age’,’sex’,’cp’,’trestbps’,’chol’,’fbs’,…
‘restecg’,’thalach’,’exang’,’oldpeak’,…
‘slope’,’ca’,’thal’});

%Prediction
label = app.modelData.trainedModel.predictFcn(T);

% Display result
if label == 0
app.ResultLabel.Text = ‘No Heart Disease’;
app.ResultLabel.FontColor = [0 1 0]; % Green
else
app.ResultLabel.Text = ‘Heart Disease Detected’;
app.ResultLabel.FontColor = [1 0 0]; % Red
end Hello everyone.
I want to ask a question regarding my final year project.
I’m currently doing a prediction system using:
UCI heart disease dataset.
Ensemble method (Subspace Discriminant) trained model from Classifier Learner App.
a GUI from app designer.
The system shown no problem when detecting a high parameter for high risk patient data and correctly shows ‘Heart Disease Detected’ but for a low parameter for a normal patient data it still shows the output as ‘Heart Disease Detected’. It is because of the dataset’s value comes from patients that already suspect with heart disease or the model used is sensitive. The GUI screenshot is suppose to be a normal patient data.
If you have an insight about this please share with me. Thank you.
I’ll share the coding used in the app designer and the GUI with some of the patient attribute data where the target is suppose to be the outcome of this system prediction.
properties (Access = private)
modelData = load(‘HeartModel.mat’,’trainedModel’);
end

methods (Access = private)

function startupFcn(app)

% Set DropDown items and ItemsData for numerical values

% Sex
app.SexDropDown.Items = {‘Female’, ‘Male’};
app.SexDropDown.ItemsData = [0, 1];

% Chest Pain (cp)
app.ChestPainDropDown.Items = {‘Normal’,’Typical Angina’, ‘Atypical Angina’, ‘Non-anginal Pain’, ‘Asymptomatic’};
app.ChestPainDropDown.ItemsData = [0, 1, 2, 3, 4];

% Fasting Blood Sugar (fbs)
app.FastingBloodSugarDropDown.Items = {‘<= 120 mg/dL’, ‘> 120 mg/dL’};
app.FastingBloodSugarDropDown.ItemsData = [0, 1];

% Rest ECG (restecg)
app.RestECGDropDown.Items = {‘Normal’, ‘ST-T Wave Abnormality’, ‘LV Hypertrophy’};
app.RestECGDropDown.ItemsData = [0, 1, 2];

% Slope
app.SlopeDropDown.Items = {‘Upsloping’, ‘Flat’, ‘Downsloping’};
app.SlopeDropDown.ItemsData = [1, 2, 3];

% Exercise Angina (exang)
app.ExerciseAnginaDropDown.Items = {‘No’, ‘Yes’};
app.ExerciseAnginaDropDown.ItemsData = [0, 1];

% CA
app.CADropDown.Items = {‘0’, ‘1’, ‘2’, ‘3’};
app.CADropDown.ItemsData = [0, 1, 2, 3];

% Thal
app.ThalDropDown.Items = {‘Normal’, ‘Fixed Defect’, ‘Reversible Defect’};
app.ThalDropDown.ItemsData = [3, 6, 7];

end
end

% Button pushed function: PredictButton
function PredictButtonPushed(app, event)

% Collect all inputs (convert to double to be safe)
age = double(app.AgeEditField.Value);
sex = double(app.SexDropDown.Value);
cp = double(app.ChestPainDropDown.Value);
trestbps = double(app.RestingBPEditField.Value);
chol = double(app.CholesterolEditField.Value);
fbs = double(app.FastingBloodSugarDropDown.Value);
restecg = double(app.RestECGDropDown.Value);
thalach = double(app.MaxHeartRateEditField.Value);
exang = double(app.ExerciseAnginaDropDown.Value);
oldpeak = double(app.OldpeakEditField.Value);
slope = double(app.SlopeDropDown.Value);
ca = double(app.CADropDown.Value);
thal = double(app.ThalDropDown.Value);

% Create input table
T = table(age, sex, cp, trestbps, chol, fbs, restecg, thalach, …
exang, oldpeak, slope, ca, thal, …
‘VariableNames’, {‘age’,’sex’,’cp’,’trestbps’,’chol’,’fbs’,…
‘restecg’,’thalach’,’exang’,’oldpeak’,…
‘slope’,’ca’,’thal’});

%Prediction
label = app.modelData.trainedModel.predictFcn(T);

% Display result
if label == 0
app.ResultLabel.Text = ‘No Heart Disease’;
app.ResultLabel.FontColor = [0 1 0]; % Green
else
app.ResultLabel.Text = ‘Heart Disease Detected’;
app.ResultLabel.FontColor = [1 0 0]; % Red
end app designer, appdesigner MATLAB Answers — New Questions

​

Is there a way, in appdesigner, to create a class-related function, i.e., a function that is local to the app’s classdef file, but which is not a class method?Is there a way, in appdesigner, to create a class-related function, i.e., a function that is local to the app’s classdef file, but which is not a class method? Is there a way, in appdesigner, to create a class-related function, i.e., a function that is local to the app’s classdef file, but which is not a class method? appdesigner, classdef, class-related, app MATLAB Answers — New Questions

​

Hello,

I am working on a FDMA project using Simulink and I am facing technical issues with the following blocks:
– Sine Wave (Discrete Time)
– Product (BPSK × Carrier)
– Bandpass Filter
– AWGN Channel

**Problem:**
1. When using AWGN Channel with mode "Signal to Noise Ratio", I get:
"Input and output must be discrete when mode set to Signal to Noise Ratio".
2. After the Filter, sometimes complex signals appear causing errors in Integrator or Decision blocks.

**Current settings for User 1 example:**
– Sine Wave: Discrete, Sample time = 0.0001 s
– Filter: Bandpass, Filter order = 4, Lower passband = 900 Hz, Upper passband = 1100 Hz
– Stopband 1 = 800 Hz, Stopband 2 = 1200 Hz, Stopband attenuation = 40 dB
– AWGN Channel: Mode = Signal to Noise Ratio

**Goal:**
– Run FDMA for two users (User1 = 1 kHz, User2 = 2 kHz)
– Avoid any complex signals
– Make AWGN Channel work correctly with specified SNR

**Request:**
– How to set up the blocks (Sine Wave, Product, Filter, AWGN) so that no complex signals appear and AWGN works correctly?
– How to choose the correct Sample time and Filter type for each block?

**Attachments:**
– Simulink screenshots
– Simulink file (.slx) if possible

Thank you very much for your help.

<<

<</matlabcentral/answers/uploaded_files/1845240/IMG_20260101_225640_567.jpg>>

>>Hello,

I am working on a FDMA project using Simulink and I am facing technical issues with the following blocks:
– Sine Wave (Discrete Time)
– Product (BPSK × Carrier)
– Bandpass Filter
– AWGN Channel

**Problem:**
1. When using AWGN Channel with mode "Signal to Noise Ratio", I get:
"Input and output must be discrete when mode set to Signal to Noise Ratio".
2. After the Filter, sometimes complex signals appear causing errors in Integrator or Decision blocks.

**Current settings for User 1 example:**
– Sine Wave: Discrete, Sample time = 0.0001 s
– Filter: Bandpass, Filter order = 4, Lower passband = 900 Hz, Upper passband = 1100 Hz
– Stopband 1 = 800 Hz, Stopband 2 = 1200 Hz, Stopband attenuation = 40 dB
– AWGN Channel: Mode = Signal to Noise Ratio

**Goal:**
– Run FDMA for two users (User1 = 1 kHz, User2 = 2 kHz)
– Avoid any complex signals
– Make AWGN Channel work correctly with specified SNR

**Request:**
– How to set up the blocks (Sine Wave, Product, Filter, AWGN) so that no complex signals appear and AWGN works correctly?
– How to choose the correct Sample time and Filter type for each block?

**Attachments:**
– Simulink screenshots
– Simulink file (.slx) if possible

Thank you very much for your help.

<<

<</matlabcentral/answers/uploaded_files/1845240/IMG_20260101_225640_567.jpg>>

>> Hello,

I am working on a FDMA project using Simulink and I am facing technical issues with the following blocks:
– Sine Wave (Discrete Time)
– Product (BPSK × Carrier)
– Bandpass Filter
– AWGN Channel

**Problem:**
1. When using AWGN Channel with mode "Signal to Noise Ratio", I get:
"Input and output must be discrete when mode set to Signal to Noise Ratio".
2. After the Filter, sometimes complex signals appear causing errors in Integrator or Decision blocks.

**Current settings for User 1 example:**
– Sine Wave: Discrete, Sample time = 0.0001 s
– Filter: Bandpass, Filter order = 4, Lower passband = 900 Hz, Upper passband = 1100 Hz
– Stopband 1 = 800 Hz, Stopband 2 = 1200 Hz, Stopband attenuation = 40 dB
– AWGN Channel: Mode = Signal to Noise Ratio

**Goal:**
– Run FDMA for two users (User1 = 1 kHz, User2 = 2 kHz)
– Avoid any complex signals
– Make AWGN Channel work correctly with specified SNR

**Request:**
– How to set up the blocks (Sine Wave, Product, Filter, AWGN) so that no complex signals appear and AWGN works correctly?
– How to choose the correct Sample time and Filter type for each block?

**Attachments:**
– Simulink screenshots
– Simulink file (.slx) if possible

Thank you very much for your help.

<<

<</matlabcentral/answers/uploaded_files/1845240/IMG_20260101_225640_567.jpg>>

>> #fdma#simulink MATLAB Answers — New Questions

​

Hey, I am using a model which I have estimated with fitglme. I want to report effect sizes and confidence intervals. Would the best way be to report OR terms and their respective intervals?
I am calculating them the following way:
[beta,~,stats] = fixedEffects(glme_best);
CI = coefCI(glme_best);
names = glme_best.CoefficientNames(:);
OR = exp(beta);
CI_OR = exp(CI);
Is that correct or is there a better way to directly get OR terms in Matlab?

Best!Hey, I am using a model which I have estimated with fitglme. I want to report effect sizes and confidence intervals. Would the best way be to report OR terms and their respective intervals?
I am calculating them the following way:
[beta,~,stats] = fixedEffects(glme_best);
CI = coefCI(glme_best);
names = glme_best.CoefficientNames(:);
OR = exp(beta);
CI_OR = exp(CI);
Is that correct or is there a better way to directly get OR terms in Matlab?

Best! Hey, I am using a model which I have estimated with fitglme. I want to report effect sizes and confidence intervals. Would the best way be to report OR terms and their respective intervals?
I am calculating them the following way:
[beta,~,stats] = fixedEffects(glme_best);
CI = coefCI(glme_best);
names = glme_best.CoefficientNames(:);
OR = exp(beta);
CI_OR = exp(CI);
Is that correct or is there a better way to directly get OR terms in Matlab?

Best! fitglme, oddsratio MATLAB Answers — New Questions

​

I can not understand which is the reason why the fitlm using variables without zscoring returns pvalues equal to NaN, whereas this does not happen using zscored variables. Below you can find the code I used:
medians_var1_scored = nanzscore(medians_var1);
medians_var2_scored = nanzscore(medians_var2);

medians_var1_scored_tr = medians_var1_scored’;
medians_var2_scored_tr = medians_var2_scored’;

tbl=table(medians_var1_scored_tr,medians_var2_scored_tr,’VariableNames’, …
{‘var1′,’var2’});
%build your model
mdl=fitlm(tbl,’var1 ~ var2′,’RobustOpts’,’on’)
which gives this result:
mdl =

Linear regression model (robust fit):
var1 ~ 1 + var2

Estimated Coefficients:
Estimate SE tStat pValue
_________ ________ ________ _______

(Intercept) 0.028674 0.094595 0.30312 0.76234
var2 -0.072919 0.094998 -0.76758 0.44429

Number of observations: 118, Error degrees of freedom: 116
Root Mean Squared Error: 1.03
R-squared: 0.00584, Adjusted R-Squared: -0.00273
F-statistic vs. constant model: 0.681, p-value = 0.411
If instead I use the original variables, I do:
tbl=table(medians_var1′,medians_var2′,’VariableNames’, …
{‘var1′,’var2’});
%build your model
mdl=fitlm(tbl,’var1 ~ var2′,’RobustOpts’,’on’)
and obtain:
mdl =

Linear regression model (robust fit):
var1 ~ 1 + var2

Estimated Coefficients:
Estimate SE tStat pValue
__________ __________ ______ __________

(Intercept) 0 0 NaN NaN
var2 8.6386e-13 2.1087e-14 40.966 7.8796e-71

Number of observations: 118, Error degrees of freedom: 117
Root Mean Squared Error: 31.4
R-squared: 0.263, Adjusted R-Squared: 0.263
F-statistic vs. constant model: Inf, p-value = NaN
I can’t understand why this happens. You can find attached both the original var1 and var2 variables and the zscored ones. But If I plot both of them, I obtain the same plot (just rescaled). Hence, there shouldn’t be a problem in the nanzscore function which is "hand written".I can not understand which is the reason why the fitlm using variables without zscoring returns pvalues equal to NaN, whereas this does not happen using zscored variables. Below you can find the code I used:
medians_var1_scored = nanzscore(medians_var1);
medians_var2_scored = nanzscore(medians_var2);

medians_var1_scored_tr = medians_var1_scored’;
medians_var2_scored_tr = medians_var2_scored’;

tbl=table(medians_var1_scored_tr,medians_var2_scored_tr,’VariableNames’, …
{‘var1′,’var2’});
%build your model
mdl=fitlm(tbl,’var1 ~ var2′,’RobustOpts’,’on’)
which gives this result:
mdl =

Linear regression model (robust fit):
var1 ~ 1 + var2

Estimated Coefficients:
Estimate SE tStat pValue
_________ ________ ________ _______

(Intercept) 0.028674 0.094595 0.30312 0.76234
var2 -0.072919 0.094998 -0.76758 0.44429

Number of observations: 118, Error degrees of freedom: 116
Root Mean Squared Error: 1.03
R-squared: 0.00584, Adjusted R-Squared: -0.00273
F-statistic vs. constant model: 0.681, p-value = 0.411
If instead I use the original variables, I do:
tbl=table(medians_var1′,medians_var2′,’VariableNames’, …
{‘var1′,’var2’});
%build your model
mdl=fitlm(tbl,’var1 ~ var2′,’RobustOpts’,’on’)
and obtain:
mdl =

Linear regression model (robust fit):
var1 ~ 1 + var2

Estimated Coefficients:
Estimate SE tStat pValue
__________ __________ ______ __________

(Intercept) 0 0 NaN NaN
var2 8.6386e-13 2.1087e-14 40.966 7.8796e-71

Number of observations: 118, Error degrees of freedom: 117
Root Mean Squared Error: 31.4
R-squared: 0.263, Adjusted R-Squared: 0.263
F-statistic vs. constant model: Inf, p-value = NaN
I can’t understand why this happens. You can find attached both the original var1 and var2 variables and the zscored ones. But If I plot both of them, I obtain the same plot (just rescaled). Hence, there shouldn’t be a problem in the nanzscore function which is "hand written". I can not understand which is the reason why the fitlm using variables without zscoring returns pvalues equal to NaN, whereas this does not happen using zscored variables. Below you can find the code I used:
medians_var1_scored = nanzscore(medians_var1);
medians_var2_scored = nanzscore(medians_var2);

medians_var1_scored_tr = medians_var1_scored’;
medians_var2_scored_tr = medians_var2_scored’;

tbl=table(medians_var1_scored_tr,medians_var2_scored_tr,’VariableNames’, …
{‘var1′,’var2’});
%build your model
mdl=fitlm(tbl,’var1 ~ var2′,’RobustOpts’,’on’)
which gives this result:
mdl =

Linear regression model (robust fit):
var1 ~ 1 + var2

Estimated Coefficients:
Estimate SE tStat pValue
_________ ________ ________ _______

(Intercept) 0.028674 0.094595 0.30312 0.76234
var2 -0.072919 0.094998 -0.76758 0.44429

Number of observations: 118, Error degrees of freedom: 116
Root Mean Squared Error: 1.03
R-squared: 0.00584, Adjusted R-Squared: -0.00273
F-statistic vs. constant model: 0.681, p-value = 0.411
If instead I use the original variables, I do:
tbl=table(medians_var1′,medians_var2′,’VariableNames’, …
{‘var1′,’var2’});
%build your model
mdl=fitlm(tbl,’var1 ~ var2′,’RobustOpts’,’on’)
and obtain:
mdl =

Linear regression model (robust fit):
var1 ~ 1 + var2

Estimated Coefficients:
Estimate SE tStat pValue
__________ __________ ______ __________

(Intercept) 0 0 NaN NaN
var2 8.6386e-13 2.1087e-14 40.966 7.8796e-71

Number of observations: 118, Error degrees of freedom: 117
Root Mean Squared Error: 31.4
R-squared: 0.263, Adjusted R-Squared: 0.263
F-statistic vs. constant model: Inf, p-value = NaN
I can’t understand why this happens. You can find attached both the original var1 and var2 variables and the zscored ones. But If I plot both of them, I obtain the same plot (just rescaled). Hence, there shouldn’t be a problem in the nanzscore function which is "hand written". fitlm, zscore, pvalue MATLAB Answers — New Questions

​

I’m trying to create a Docker container that has MATLAB installed in it. The images on Docker Hub seem to only download MATLAB at the latest update level. How can I put, for example, R2022b Update 3 into a container?I’m trying to create a Docker container that has MATLAB installed in it. The images on Docker Hub seem to only download MATLAB at the latest update level. How can I put, for example, R2022b Update 3 into a container? I’m trying to create a Docker container that has MATLAB installed in it. The images on Docker Hub seem to only download MATLAB at the latest update level. How can I put, for example, R2022b Update 3 into a container?  MATLAB Answers — New Questions

​

Hello experts
I am trying to automate my toolbox creation in gitlab ci and trying to find the best way to do this.
I looked at using the matlab runtime docker for my purpose, looking at the documentation it says matlab runtime docker is used for executing matlab apps, can i also use it to build the toolbox?
Do i need to use the matlab docker with license to build the toolbox?
Is there a lighter matlab installation that serves the purpose?
Any guidance will be appreciated.
ThanksHello experts
I am trying to automate my toolbox creation in gitlab ci and trying to find the best way to do this.
I looked at using the matlab runtime docker for my purpose, looking at the documentation it says matlab runtime docker is used for executing matlab apps, can i also use it to build the toolbox?
Do i need to use the matlab docker with license to build the toolbox?
Is there a lighter matlab installation that serves the purpose?
Any guidance will be appreciated.
Thanks Hello experts
I am trying to automate my toolbox creation in gitlab ci and trying to find the best way to do this.
I looked at using the matlab runtime docker for my purpose, looking at the documentation it says matlab runtime docker is used for executing matlab apps, can i also use it to build the toolbox?
Do i need to use the matlab docker with license to build the toolbox?
Is there a lighter matlab installation that serves the purpose?
Any guidance will be appreciated.
Thanks toolbox, cli MATLAB Answers — New Questions

​

Hi All

I have already calculated the gains for acceleration and velocity but my block is state space and gives displacement and velocity. I just dont know , what should I do with displacement, or should I leave disp and vel and only control acceleration with one gain or acc and vel ?? I have added 2 Zero pole blocks, which defined the new gains. but then It seems like State Space is not coincident with this methodHi All

I have already calculated the gains for acceleration and velocity but my block is state space and gives displacement and velocity. I just dont know , what should I do with displacement, or should I leave disp and vel and only control acceleration with one gain or acc and vel ?? I have added 2 Zero pole blocks, which defined the new gains. but then It seems like State Space is not coincident with this method Hi All

I have already calculated the gains for acceleration and velocity but my block is state space and gives displacement and velocity. I just dont know , what should I do with displacement, or should I leave disp and vel and only control acceleration with one gain or acc and vel ?? I have added 2 Zero pole blocks, which defined the new gains. but then It seems like State Space is not coincident with this method simulink, control MATLAB Answers — New Questions

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After opening a specific .mlapp, each time I go back to the file tab inside appdesigner, I receive an dialog window : "The file has been modified outside of MATLAB Editor. Do you want to reload it?"
I have this problem only with one specific mlapp file. I have other mlapp files in the same directory for which this issue does not appear.
All these mlapp files are saved locally. They were created from guide apps, using Matlab migration tool.
This issue appears since the mlapp file creation with all the different Matlab releases I used since (R2025a on Linux now).After opening a specific .mlapp, each time I go back to the file tab inside appdesigner, I receive an dialog window : "The file has been modified outside of MATLAB Editor. Do you want to reload it?"
I have this problem only with one specific mlapp file. I have other mlapp files in the same directory for which this issue does not appear.
All these mlapp files are saved locally. They were created from guide apps, using Matlab migration tool.
This issue appears since the mlapp file creation with all the different Matlab releases I used since (R2025a on Linux now). After opening a specific .mlapp, each time I go back to the file tab inside appdesigner, I receive an dialog window : "The file has been modified outside of MATLAB Editor. Do you want to reload it?"
I have this problem only with one specific mlapp file. I have other mlapp files in the same directory for which this issue does not appear.
All these mlapp files are saved locally. They were created from guide apps, using Matlab migration tool.
This issue appears since the mlapp file creation with all the different Matlab releases I used since (R2025a on Linux now). appdesigner MATLAB Answers — New Questions

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I have a point cloud file in the .pcd format. I want to calculate a Voronoi diagram for this .pcd file. I also have a set of points with x and y coordinates that were extracted from the .pcd file. I want to calculate the Voronoi diagram based on these x and y coordinates. My objective is to divide the point cloud into zones corresponding to these points (x, y). So far, I have written the following code but it seems like there is no connection between the point cloud and x-y coordinates. How can I relate the point cloud and the co ordinates?
ptCloud = pcread("test_obj6.pcd");
x = [ 7.0267 4.8436 4.8767 2.8000];
y = [ 4.2001 4.5947 2.1412 3.2000];
voronoi(x,y)I have a point cloud file in the .pcd format. I want to calculate a Voronoi diagram for this .pcd file. I also have a set of points with x and y coordinates that were extracted from the .pcd file. I want to calculate the Voronoi diagram based on these x and y coordinates. My objective is to divide the point cloud into zones corresponding to these points (x, y). So far, I have written the following code but it seems like there is no connection between the point cloud and x-y coordinates. How can I relate the point cloud and the co ordinates?
ptCloud = pcread("test_obj6.pcd");
x = [ 7.0267 4.8436 4.8767 2.8000];
y = [ 4.2001 4.5947 2.1412 3.2000];
voronoi(x,y) I have a point cloud file in the .pcd format. I want to calculate a Voronoi diagram for this .pcd file. I also have a set of points with x and y coordinates that were extracted from the .pcd file. I want to calculate the Voronoi diagram based on these x and y coordinates. My objective is to divide the point cloud into zones corresponding to these points (x, y). So far, I have written the following code but it seems like there is no connection between the point cloud and x-y coordinates. How can I relate the point cloud and the co ordinates?
ptCloud = pcread("test_obj6.pcd");
x = [ 7.0267 4.8436 4.8767 2.8000];
y = [ 4.2001 4.5947 2.1412 3.2000];
voronoi(x,y) matlab MATLAB Answers — New Questions

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