Hello,
I have a matrix organized in this way:
M= col1, col2…. col10
col1 and col2 are the x and y position of the data, col10 is a property of this data and it is a number.
I would like to use the numbers in col10 to make a colormap and assign ot every point a specific color that depends on the value in col10.
I did this long time ago, but I don’t remember how, can somebody help me, please?

Thanks
F.Hello,
I have a matrix organized in this way:
M= col1, col2…. col10
col1 and col2 are the x and y position of the data, col10 is a property of this data and it is a number.
I would like to use the numbers in col10 to make a colormap and assign ot every point a specific color that depends on the value in col10.
I did this long time ago, but I don’t remember how, can somebody help me, please?

Thanks
F. Hello,
I have a matrix organized in this way:
M= col1, col2…. col10
col1 and col2 are the x and y position of the data, col10 is a property of this data and it is a number.
I would like to use the numbers in col10 to make a colormap and assign ot every point a specific color that depends on the value in col10.
I did this long time ago, but I don’t remember how, can somebody help me, please?

Thanks
F. plot MATLAB Answers — New Questions

​

As the rules introduced, our minidrone will be tested on multiple tracks. Does anyone know who we can build our own tracks for evaluation in the simulink?As the rules introduced, our minidrone will be tested on multiple tracks. Does anyone know who we can build our own tracks for evaluation in the simulink? As the rules introduced, our minidrone will be tested on multiple tracks. Does anyone know who we can build our own tracks for evaluation in the simulink? minidronecompetition MATLAB Answers — New Questions

​

Hi, Im trying to find the orientation that is roll and pitch angle of my platform by analysing the overall geometery of the dots. To do so i have firstly detected the dots by using standard deviation and k-means clustering and dividing the image into 5×5 boxes then a plane fitting curve method is used to determine the overall geometery of the dots which further gives orientation of the plate. The obtained angles are incorrect what might have possibly gone wrong please help and suggest any possible solution. I’m actually trying to implement a blass on a plate system and i want to detect the orientation of the plate using webcam. Also im using MATLAB 2021a therefore im not sure how to calibrate my camera for such a pattern. The MATLAB code is given below;
clear all;
clc;
close all;
% Create a webcam object
cap = webcam(‘Adesso CyberTrack H3’);
% Adjust camera settings if supported
try
% Set the exposure time (shutter speed) in seconds
exposureTime = 0.01; % Adjust as needed
cap.ExposureMode = ‘manual’;
cap.Exposure = exposureTime;
catch ME
disp(‘Warning: Unable to set exposure time for the camera.’);
disp(ME.message);
end

% Create the background subtractor object for ball detection
back_sub = vision.ForegroundDetector(‘NumTrainingFrames’, 100, ‘NumGaussians’, 3, ‘MinimumBackgroundRatio’, 0.7);
% Create structuring element for morphological operation
se = strel(‘rectangle’, [20, 20]);

% Initialize calibration values
calibration_pitch = 0;
calibration_roll = 0;

% Calibrate the system to set initial pitch and roll to zero
frame = snapshot(cap);
I_gray = rgb2gray(frame);
I_contrast = imadjust(I_gray);
bw = imbinarize(I_contrast, ‘adaptive’);
bw_filled = imfill(bw, ‘holes’);
bw_cleaned = bwareaopen(bw_filled, 50);
stats = regionprops(‘table’, bw_cleaned, ‘Centroid’, ‘BoundingBox’);
centroids = stats.Centroid;

if size(centroids, 1) >= 3
X = centroids(:, 1);
Y = centroids(:, 2);
Z = linspace(0, 1, size(centroids, 1))’;
A = [X, Y, ones(size(X))];
coeffs = A Z;
normal = [-coeffs(1), -coeffs(2), 1];
normal = normal / norm(normal);
calibration_pitch = asin(normal(1));
calibration_roll = asin(normal(2));
disp([‘Calibration Pitch: ‘, num2str(calibration_pitch), ‘ degrees’]);
disp([‘Calibration Roll: ‘, num2str(calibration_roll), ‘ degrees’]);
else
disp(‘Not enough dots detected for calibration.’);
end

while true
% Read frame from webcam
frame = snapshot(cap);

% Part 1: Dot Detection and Tilt Angle Calculation
I_gray = rgb2gray(frame);
I_contrast = imadjust(I_gray);
bw = imbinarize(I_contrast, ‘adaptive’);
bw_filled = imfill(bw, ‘holes’);
bw_cleaned = bwareaopen(bw_filled, 50);
stats = regionprops(‘table’, bw_cleaned, ‘Centroid’, ‘BoundingBox’);
centroids = stats.Centroid;
boundingBoxes = stats.BoundingBox;

if size(centroids, 1) >= 3
X = centroids(:, 1);
Y = centroids(:, 2);
Z = linspace(0, 1, size(centroids, 1))’;
A = [X, Y, ones(size(X))];
coeffs = A Z;
normal = [-coeffs(1), -coeffs(2), 1];
normal = normal / norm(normal);
pitch = asin(normal(1)) – calibration_pitch;
roll = asin(normal(2)) – calibration_roll;
yaw = 0;

disp([‘Pitch (Tilt around Y-axis): ‘, num2str(pitch), ‘ degrees’]);
disp([‘Roll (Tilt around X-axis): ‘, num2str(roll), ‘ degrees’]);
disp([‘Yaw (Rotation around Z-axis): ‘, num2str(yaw), ‘ degrees’]);
else
pitch = 0;
roll = 0;
yaw = 0;
disp(‘Not enough dots detected to fit a plane.’);
end

for i = 1:size(boundingBoxes, 1)
frame = insertShape(frame, ‘Rectangle’, boundingBoxes(i, :), ‘Color’, ‘g’, ‘LineWidth’, 2);
end

fg_mask = step(back_sub, frame);
fg_mask = imclose(fg_mask, se);
fg_mask = medfilt2(fg_mask, [5, 5]);
fg_mask = uint8(fg_mask) * 255;
[contours, ~] = bwlabel(fg_mask);
stats = regionprops(contours, ‘Area’, ‘BoundingBox’, ‘Centroid’);

if ~isempty(stats)
[~, max_index] = max([stats.Area]);
centroid = stats(max_index).Centroid;
boundingBox = stats(max_index).BoundingBox;
frame = insertShape(frame, ‘Rectangle’, boundingBox, ‘Color’, [0, 255, 0], ‘LineWidth’, 3);
text = [‘x: ‘, num2str(centroid(1)), ‘, y: ‘, num2str(centroid(2))];
frame = insertText(frame, [centroid(1) – 10, centroid(2) – 10], text, ‘FontSize’, 50, ‘TextColor’, [0, 255, 0]);
coordinates = [];
coordinates = [coordinates; centroid];
disp(coordinates);
end

frame = insertText(frame, [10, 10], [‘Pitch: ‘, num2str(pitch), ‘°’], ‘FontSize’, 18, ‘BoxColor’, ‘red’, ‘TextColor’, ‘white’);
frame = insertText(frame, [10, 40], [‘Roll: ‘, num2str(roll), ‘°’], ‘FontSize’, 18, ‘BoxColor’, ‘red’, ‘TextColor’, ‘white’);
frame = insertText(frame, [10, 70], [‘Yaw: ‘, num2str(yaw), ‘°’], ‘FontSize’, 18, ‘BoxColor’, ‘red’, ‘TextColor’, ‘white’);
imshow(frame);
pause(0.0001);
end
clear cap;Hi, Im trying to find the orientation that is roll and pitch angle of my platform by analysing the overall geometery of the dots. To do so i have firstly detected the dots by using standard deviation and k-means clustering and dividing the image into 5×5 boxes then a plane fitting curve method is used to determine the overall geometery of the dots which further gives orientation of the plate. The obtained angles are incorrect what might have possibly gone wrong please help and suggest any possible solution. I’m actually trying to implement a blass on a plate system and i want to detect the orientation of the plate using webcam. Also im using MATLAB 2021a therefore im not sure how to calibrate my camera for such a pattern. The MATLAB code is given below;
clear all;
clc;
close all;
% Create a webcam object
cap = webcam(‘Adesso CyberTrack H3’);
% Adjust camera settings if supported
try
% Set the exposure time (shutter speed) in seconds
exposureTime = 0.01; % Adjust as needed
cap.ExposureMode = ‘manual’;
cap.Exposure = exposureTime;
catch ME
disp(‘Warning: Unable to set exposure time for the camera.’);
disp(ME.message);
end

% Create the background subtractor object for ball detection
back_sub = vision.ForegroundDetector(‘NumTrainingFrames’, 100, ‘NumGaussians’, 3, ‘MinimumBackgroundRatio’, 0.7);
% Create structuring element for morphological operation
se = strel(‘rectangle’, [20, 20]);

% Initialize calibration values
calibration_pitch = 0;
calibration_roll = 0;

% Calibrate the system to set initial pitch and roll to zero
frame = snapshot(cap);
I_gray = rgb2gray(frame);
I_contrast = imadjust(I_gray);
bw = imbinarize(I_contrast, ‘adaptive’);
bw_filled = imfill(bw, ‘holes’);
bw_cleaned = bwareaopen(bw_filled, 50);
stats = regionprops(‘table’, bw_cleaned, ‘Centroid’, ‘BoundingBox’);
centroids = stats.Centroid;

if size(centroids, 1) >= 3
X = centroids(:, 1);
Y = centroids(:, 2);
Z = linspace(0, 1, size(centroids, 1))’;
A = [X, Y, ones(size(X))];
coeffs = A Z;
normal = [-coeffs(1), -coeffs(2), 1];
normal = normal / norm(normal);
calibration_pitch = asin(normal(1));
calibration_roll = asin(normal(2));
disp([‘Calibration Pitch: ‘, num2str(calibration_pitch), ‘ degrees’]);
disp([‘Calibration Roll: ‘, num2str(calibration_roll), ‘ degrees’]);
else
disp(‘Not enough dots detected for calibration.’);
end

while true
% Read frame from webcam
frame = snapshot(cap);

% Part 1: Dot Detection and Tilt Angle Calculation
I_gray = rgb2gray(frame);
I_contrast = imadjust(I_gray);
bw = imbinarize(I_contrast, ‘adaptive’);
bw_filled = imfill(bw, ‘holes’);
bw_cleaned = bwareaopen(bw_filled, 50);
stats = regionprops(‘table’, bw_cleaned, ‘Centroid’, ‘BoundingBox’);
centroids = stats.Centroid;
boundingBoxes = stats.BoundingBox;

if size(centroids, 1) >= 3
X = centroids(:, 1);
Y = centroids(:, 2);
Z = linspace(0, 1, size(centroids, 1))’;
A = [X, Y, ones(size(X))];
coeffs = A Z;
normal = [-coeffs(1), -coeffs(2), 1];
normal = normal / norm(normal);
pitch = asin(normal(1)) – calibration_pitch;
roll = asin(normal(2)) – calibration_roll;
yaw = 0;

disp([‘Pitch (Tilt around Y-axis): ‘, num2str(pitch), ‘ degrees’]);
disp([‘Roll (Tilt around X-axis): ‘, num2str(roll), ‘ degrees’]);
disp([‘Yaw (Rotation around Z-axis): ‘, num2str(yaw), ‘ degrees’]);
else
pitch = 0;
roll = 0;
yaw = 0;
disp(‘Not enough dots detected to fit a plane.’);
end

for i = 1:size(boundingBoxes, 1)
frame = insertShape(frame, ‘Rectangle’, boundingBoxes(i, :), ‘Color’, ‘g’, ‘LineWidth’, 2);
end

fg_mask = step(back_sub, frame);
fg_mask = imclose(fg_mask, se);
fg_mask = medfilt2(fg_mask, [5, 5]);
fg_mask = uint8(fg_mask) * 255;
[contours, ~] = bwlabel(fg_mask);
stats = regionprops(contours, ‘Area’, ‘BoundingBox’, ‘Centroid’);

if ~isempty(stats)
[~, max_index] = max([stats.Area]);
centroid = stats(max_index).Centroid;
boundingBox = stats(max_index).BoundingBox;
frame = insertShape(frame, ‘Rectangle’, boundingBox, ‘Color’, [0, 255, 0], ‘LineWidth’, 3);
text = [‘x: ‘, num2str(centroid(1)), ‘, y: ‘, num2str(centroid(2))];
frame = insertText(frame, [centroid(1) – 10, centroid(2) – 10], text, ‘FontSize’, 50, ‘TextColor’, [0, 255, 0]);
coordinates = [];
coordinates = [coordinates; centroid];
disp(coordinates);
end

frame = insertText(frame, [10, 10], [‘Pitch: ‘, num2str(pitch), ‘°’], ‘FontSize’, 18, ‘BoxColor’, ‘red’, ‘TextColor’, ‘white’);
frame = insertText(frame, [10, 40], [‘Roll: ‘, num2str(roll), ‘°’], ‘FontSize’, 18, ‘BoxColor’, ‘red’, ‘TextColor’, ‘white’);
frame = insertText(frame, [10, 70], [‘Yaw: ‘, num2str(yaw), ‘°’], ‘FontSize’, 18, ‘BoxColor’, ‘red’, ‘TextColor’, ‘white’);
imshow(frame);
pause(0.0001);
end
clear cap; Hi, Im trying to find the orientation that is roll and pitch angle of my platform by analysing the overall geometery of the dots. To do so i have firstly detected the dots by using standard deviation and k-means clustering and dividing the image into 5×5 boxes then a plane fitting curve method is used to determine the overall geometery of the dots which further gives orientation of the plate. The obtained angles are incorrect what might have possibly gone wrong please help and suggest any possible solution. I’m actually trying to implement a blass on a plate system and i want to detect the orientation of the plate using webcam. Also im using MATLAB 2021a therefore im not sure how to calibrate my camera for such a pattern. The MATLAB code is given below;
clear all;
clc;
close all;
% Create a webcam object
cap = webcam(‘Adesso CyberTrack H3’);
% Adjust camera settings if supported
try
% Set the exposure time (shutter speed) in seconds
exposureTime = 0.01; % Adjust as needed
cap.ExposureMode = ‘manual’;
cap.Exposure = exposureTime;
catch ME
disp(‘Warning: Unable to set exposure time for the camera.’);
disp(ME.message);
end

% Create the background subtractor object for ball detection
back_sub = vision.ForegroundDetector(‘NumTrainingFrames’, 100, ‘NumGaussians’, 3, ‘MinimumBackgroundRatio’, 0.7);
% Create structuring element for morphological operation
se = strel(‘rectangle’, [20, 20]);

% Initialize calibration values
calibration_pitch = 0;
calibration_roll = 0;

% Calibrate the system to set initial pitch and roll to zero
frame = snapshot(cap);
I_gray = rgb2gray(frame);
I_contrast = imadjust(I_gray);
bw = imbinarize(I_contrast, ‘adaptive’);
bw_filled = imfill(bw, ‘holes’);
bw_cleaned = bwareaopen(bw_filled, 50);
stats = regionprops(‘table’, bw_cleaned, ‘Centroid’, ‘BoundingBox’);
centroids = stats.Centroid;

if size(centroids, 1) >= 3
X = centroids(:, 1);
Y = centroids(:, 2);
Z = linspace(0, 1, size(centroids, 1))’;
A = [X, Y, ones(size(X))];
coeffs = A Z;
normal = [-coeffs(1), -coeffs(2), 1];
normal = normal / norm(normal);
calibration_pitch = asin(normal(1));
calibration_roll = asin(normal(2));
disp([‘Calibration Pitch: ‘, num2str(calibration_pitch), ‘ degrees’]);
disp([‘Calibration Roll: ‘, num2str(calibration_roll), ‘ degrees’]);
else
disp(‘Not enough dots detected for calibration.’);
end

while true
% Read frame from webcam
frame = snapshot(cap);

% Part 1: Dot Detection and Tilt Angle Calculation
I_gray = rgb2gray(frame);
I_contrast = imadjust(I_gray);
bw = imbinarize(I_contrast, ‘adaptive’);
bw_filled = imfill(bw, ‘holes’);
bw_cleaned = bwareaopen(bw_filled, 50);
stats = regionprops(‘table’, bw_cleaned, ‘Centroid’, ‘BoundingBox’);
centroids = stats.Centroid;
boundingBoxes = stats.BoundingBox;

if size(centroids, 1) >= 3
X = centroids(:, 1);
Y = centroids(:, 2);
Z = linspace(0, 1, size(centroids, 1))’;
A = [X, Y, ones(size(X))];
coeffs = A Z;
normal = [-coeffs(1), -coeffs(2), 1];
normal = normal / norm(normal);
pitch = asin(normal(1)) – calibration_pitch;
roll = asin(normal(2)) – calibration_roll;
yaw = 0;

disp([‘Pitch (Tilt around Y-axis): ‘, num2str(pitch), ‘ degrees’]);
disp([‘Roll (Tilt around X-axis): ‘, num2str(roll), ‘ degrees’]);
disp([‘Yaw (Rotation around Z-axis): ‘, num2str(yaw), ‘ degrees’]);
else
pitch = 0;
roll = 0;
yaw = 0;
disp(‘Not enough dots detected to fit a plane.’);
end

for i = 1:size(boundingBoxes, 1)
frame = insertShape(frame, ‘Rectangle’, boundingBoxes(i, :), ‘Color’, ‘g’, ‘LineWidth’, 2);
end

fg_mask = step(back_sub, frame);
fg_mask = imclose(fg_mask, se);
fg_mask = medfilt2(fg_mask, [5, 5]);
fg_mask = uint8(fg_mask) * 255;
[contours, ~] = bwlabel(fg_mask);
stats = regionprops(contours, ‘Area’, ‘BoundingBox’, ‘Centroid’);

if ~isempty(stats)
[~, max_index] = max([stats.Area]);
centroid = stats(max_index).Centroid;
boundingBox = stats(max_index).BoundingBox;
frame = insertShape(frame, ‘Rectangle’, boundingBox, ‘Color’, [0, 255, 0], ‘LineWidth’, 3);
text = [‘x: ‘, num2str(centroid(1)), ‘, y: ‘, num2str(centroid(2))];
frame = insertText(frame, [centroid(1) – 10, centroid(2) – 10], text, ‘FontSize’, 50, ‘TextColor’, [0, 255, 0]);
coordinates = [];
coordinates = [coordinates; centroid];
disp(coordinates);
end

frame = insertText(frame, [10, 10], [‘Pitch: ‘, num2str(pitch), ‘°’], ‘FontSize’, 18, ‘BoxColor’, ‘red’, ‘TextColor’, ‘white’);
frame = insertText(frame, [10, 40], [‘Roll: ‘, num2str(roll), ‘°’], ‘FontSize’, 18, ‘BoxColor’, ‘red’, ‘TextColor’, ‘white’);
frame = insertText(frame, [10, 70], [‘Yaw: ‘, num2str(yaw), ‘°’], ‘FontSize’, 18, ‘BoxColor’, ‘red’, ‘TextColor’, ‘white’);
imshow(frame);
pause(0.0001);
end
clear cap; matlab, image processing, computer vision MATLAB Answers — New Questions

​

I have implemented a simulation of a system with around 20k states in Simulink via a Matlab System using iterpreted execution (since I was lazy, I used simbolic variables in the setupImpl() function for deriving the stepImpl() function more easily). The model simulates rather slow, and thus I am thinking on what to do next to improve performance. I thought about
1) rewrite the matlab system such that I can use code generation for execution
2) use the obj.stepImpl() function in the workspace and call there an ode solver.
Do you have a guess which of the options is going to show better performance? Are there any advantages of both options? Option 2) would be much easier for me to implement.
Thanks in advance!I have implemented a simulation of a system with around 20k states in Simulink via a Matlab System using iterpreted execution (since I was lazy, I used simbolic variables in the setupImpl() function for deriving the stepImpl() function more easily). The model simulates rather slow, and thus I am thinking on what to do next to improve performance. I thought about
1) rewrite the matlab system such that I can use code generation for execution
2) use the obj.stepImpl() function in the workspace and call there an ode solver.
Do you have a guess which of the options is going to show better performance? Are there any advantages of both options? Option 2) would be much easier for me to implement.
Thanks in advance! I have implemented a simulation of a system with around 20k states in Simulink via a Matlab System using iterpreted execution (since I was lazy, I used simbolic variables in the setupImpl() function for deriving the stepImpl() function more easily). The model simulates rather slow, and thus I am thinking on what to do next to improve performance. I thought about
1) rewrite the matlab system such that I can use code generation for execution
2) use the obj.stepImpl() function in the workspace and call there an ode solver.
Do you have a guess which of the options is going to show better performance? Are there any advantages of both options? Option 2) would be much easier for me to implement.
Thanks in advance! ode, simulink, performance, code generation, interpreted execution, matlab system MATLAB Answers — New Questions

​

Hi,
I am reading data over TCP/IP from hardware device using
t1=tcpclient("xxxx",xxxx)
I am configuring callback function, so that when ever 210 data byes avaible to read function1() execute.
while t1.BytesAvailable == 0
%wait for data
end
configureCallback(t1,"byte",210,@varargin()function1())

function function1()
Bytes_DATAF1=t1.NumBytesAvailable
DATA=read(t1,210);
decode=swapbytes(typecast(uint8(DATAF1(1,7:10)’),’uint32′));
Bytes_DATAF2=t1.NumBytesAvailable
end
codes doing fine but in middle giving following warning.
Warning: Error occurred while executing the listener callback for event DataWritten
defined for class asyncio.InputStream:
Error using +
Integers can only be combined with integers of the same class, or scalar doubles.

Error in matlabshared.network.internal.TCPClient/onDataReceived

Error in
matlabshared.network.internal.TCPClient>@(varargin)obj.onDataReceived(varargin{:})

Error in asyncio.Channel/onDataReceived (line 487)
notify(obj.InputStream, ‘DataWritten’, …

Error in asyncio.Channel>@(source,data)obj.onDataReceived() (line 425)
@(source, data) obj.onDataReceived());
> In asyncio/Channel/onDataReceived (line 487)
In asyncio.Channel>@(source,data)obj.onDataReceived() (line 425)
——————————————————————————————————–

function function1()
Bytes_DATAF1=t1.NumBytesAvailable
DATA=read(t1,210);
decode=swapbytes(typecast(uint8(DATAF1(1,7:10)’),’uint32′));
Bytes_DATAF2=t1.NumBytesAvailable
end
bytes availabe to read
t1.BytesAvailable=Bytes_DATAF1 =12810
mycode reads only 210 bytes
bytes remaining to read
t1.BytesAvailable=Bytes_DATAF2 = 255
12810-255=12555 bytes missing.Hi,
I am reading data over TCP/IP from hardware device using
t1=tcpclient("xxxx",xxxx)
I am configuring callback function, so that when ever 210 data byes avaible to read function1() execute.
while t1.BytesAvailable == 0
%wait for data
end
configureCallback(t1,"byte",210,@varargin()function1())

function function1()
Bytes_DATAF1=t1.NumBytesAvailable
DATA=read(t1,210);
decode=swapbytes(typecast(uint8(DATAF1(1,7:10)’),’uint32′));
Bytes_DATAF2=t1.NumBytesAvailable
end
codes doing fine but in middle giving following warning.
Warning: Error occurred while executing the listener callback for event DataWritten
defined for class asyncio.InputStream:
Error using +
Integers can only be combined with integers of the same class, or scalar doubles.

Error in matlabshared.network.internal.TCPClient/onDataReceived

Error in
matlabshared.network.internal.TCPClient>@(varargin)obj.onDataReceived(varargin{:})

Error in asyncio.Channel/onDataReceived (line 487)
notify(obj.InputStream, ‘DataWritten’, …

Error in asyncio.Channel>@(source,data)obj.onDataReceived() (line 425)
@(source, data) obj.onDataReceived());
> In asyncio/Channel/onDataReceived (line 487)
In asyncio.Channel>@(source,data)obj.onDataReceived() (line 425)
——————————————————————————————————–

function function1()
Bytes_DATAF1=t1.NumBytesAvailable
DATA=read(t1,210);
decode=swapbytes(typecast(uint8(DATAF1(1,7:10)’),’uint32′));
Bytes_DATAF2=t1.NumBytesAvailable
end
bytes availabe to read
t1.BytesAvailable=Bytes_DATAF1 =12810
mycode reads only 210 bytes
bytes remaining to read
t1.BytesAvailable=Bytes_DATAF2 = 255
12810-255=12555 bytes missing. Hi,
I am reading data over TCP/IP from hardware device using
t1=tcpclient("xxxx",xxxx)
I am configuring callback function, so that when ever 210 data byes avaible to read function1() execute.
while t1.BytesAvailable == 0
%wait for data
end
configureCallback(t1,"byte",210,@varargin()function1())

function function1()
Bytes_DATAF1=t1.NumBytesAvailable
DATA=read(t1,210);
decode=swapbytes(typecast(uint8(DATAF1(1,7:10)’),’uint32′));
Bytes_DATAF2=t1.NumBytesAvailable
end
codes doing fine but in middle giving following warning.
Warning: Error occurred while executing the listener callback for event DataWritten
defined for class asyncio.InputStream:
Error using +
Integers can only be combined with integers of the same class, or scalar doubles.

Error in matlabshared.network.internal.TCPClient/onDataReceived

Error in
matlabshared.network.internal.TCPClient>@(varargin)obj.onDataReceived(varargin{:})

Error in asyncio.Channel/onDataReceived (line 487)
notify(obj.InputStream, ‘DataWritten’, …

Error in asyncio.Channel>@(source,data)obj.onDataReceived() (line 425)
@(source, data) obj.onDataReceived());
> In asyncio/Channel/onDataReceived (line 487)
In asyncio.Channel>@(source,data)obj.onDataReceived() (line 425)
——————————————————————————————————–

function function1()
Bytes_DATAF1=t1.NumBytesAvailable
DATA=read(t1,210);
decode=swapbytes(typecast(uint8(DATAF1(1,7:10)’),’uint32′));
Bytes_DATAF2=t1.NumBytesAvailable
end
bytes availabe to read
t1.BytesAvailable=Bytes_DATAF1 =12810
mycode reads only 210 bytes
bytes remaining to read
t1.BytesAvailable=Bytes_DATAF2 = 255
12810-255=12555 bytes missing. tcpclient, callback, configurecallback MATLAB Answers — New Questions

​

I have a system as shown in the picture. y is a scalar defined in the function(also shown in picture).

However I have received such errors. Why is this happening?
Error in port widths or dimensions. Invalid dimension has been specified for ‘input port 2’ of ‘slxlx/Add’.
Error in port widths or dimensions. ‘output port 1’ of ‘slxlx/Transfer Fcn’ is a one dimensional vector with 1 elements.I have a system as shown in the picture. y is a scalar defined in the function(also shown in picture).

However I have received such errors. Why is this happening?
Error in port widths or dimensions. Invalid dimension has been specified for ‘input port 2’ of ‘slxlx/Add’.
Error in port widths or dimensions. ‘output port 1’ of ‘slxlx/Transfer Fcn’ is a one dimensional vector with 1 elements. I have a system as shown in the picture. y is a scalar defined in the function(also shown in picture).

However I have received such errors. Why is this happening?
Error in port widths or dimensions. Invalid dimension has been specified for ‘input port 2’ of ‘slxlx/Add’.
Error in port widths or dimensions. ‘output port 1’ of ‘slxlx/Transfer Fcn’ is a one dimensional vector with 1 elements. add, matlab, simulink, sum, dimension, width MATLAB Answers — New Questions

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I build a "liquid valve" component (.ssc file) in Simscape which includes a dropdown menu to select different valve types. The parameters for each valve are stored as a structure in a separated .m file. Depending on which valve is selected, I would like to "load" the corresponding values into my "liquid valve" component (.ssc file). Similar to the "Thermal Liquid Properties (TL)" component which loads an external file depending on the selected fluid.
How do I "load/import" my external .m file (structure) into my simscape component?I build a "liquid valve" component (.ssc file) in Simscape which includes a dropdown menu to select different valve types. The parameters for each valve are stored as a structure in a separated .m file. Depending on which valve is selected, I would like to "load" the corresponding values into my "liquid valve" component (.ssc file). Similar to the "Thermal Liquid Properties (TL)" component which loads an external file depending on the selected fluid.
How do I "load/import" my external .m file (structure) into my simscape component? I build a "liquid valve" component (.ssc file) in Simscape which includes a dropdown menu to select different valve types. The parameters for each valve are stored as a structure in a separated .m file. Depending on which valve is selected, I would like to "load" the corresponding values into my "liquid valve" component (.ssc file). Similar to the "Thermal Liquid Properties (TL)" component which loads an external file depending on the selected fluid.
How do I "load/import" my external .m file (structure) into my simscape component? simscape, structures MATLAB Answers — New Questions

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I work in a visual attention lab, and we use Matlab to code lots of experiments that show many pictures with different timings, features, etc. However, our lab computers are all Mac OSs, so we’re concerned that Psychtoolbox will be essentially useless once we are required to update the OS by the institution. Are the new Matlab updates moving towards making it powerful enough to code these experiments without needing psychtoolbox?I work in a visual attention lab, and we use Matlab to code lots of experiments that show many pictures with different timings, features, etc. However, our lab computers are all Mac OSs, so we’re concerned that Psychtoolbox will be essentially useless once we are required to update the OS by the institution. Are the new Matlab updates moving towards making it powerful enough to code these experiments without needing psychtoolbox? I work in a visual attention lab, and we use Matlab to code lots of experiments that show many pictures with different timings, features, etc. However, our lab computers are all Mac OSs, so we’re concerned that Psychtoolbox will be essentially useless once we are required to update the OS by the institution. Are the new Matlab updates moving towards making it powerful enough to code these experiments without needing psychtoolbox? psychtoolbox, updates, matlab MATLAB Answers — New Questions

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Export function is saving previous result of matlab live script, and saving it is loosing all the data when overwritten.
I have a matlab live script file, and export function is included in that, however it is not saving the current run data.
is there any way to export the only data of the current state of matlab live script?Export function is saving previous result of matlab live script, and saving it is loosing all the data when overwritten.
I have a matlab live script file, and export function is included in that, however it is not saving the current run data.
is there any way to export the only data of the current state of matlab live script? Export function is saving previous result of matlab live script, and saving it is loosing all the data when overwritten.
I have a matlab live script file, and export function is included in that, however it is not saving the current run data.
is there any way to export the only data of the current state of matlab live script? export, save MATLAB Answers — New Questions

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Started learning MATLAB Fundamentals then stopped for a few months. Would like to start again.Started learning MATLAB Fundamentals then stopped for a few months. Would like to start again. Started learning MATLAB Fundamentals then stopped for a few months. Would like to start again. matlab MATLAB Answers — New Questions

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