Category: Matlab
Category Archives: Matlab
Overlap a webcam image and a heatmap.
I have a webcam image "ref2" and I want to overlap the heatmap "pp" over it. In the program I have a video preview coming from a webcam and I have to put a heatmap over it. Can anyone please help me with this?I have a webcam image "ref2" and I want to overlap the heatmap "pp" over it. In the program I have a video preview coming from a webcam and I have to put a heatmap over it. Can anyone please help me with this? I have a webcam image "ref2" and I want to overlap the heatmap "pp" over it. In the program I have a video preview coming from a webcam and I have to put a heatmap over it. Can anyone please help me with this? image analysis, image processing, image acquisition MATLAB Answers — New Questions
[Thermal Liquid library Simscape] Help for an Engine cooling model
Hey guys !
I am part of a formula student team, and decided to create a simulation and modelling department for the team, which aims to model our car in Simulink. I am pretty new to simulink/simscape, and as a first task, I wanted to model the car cooling system. The aim is to determine a required flow rates in the radiators to help the aero team to design side pods.
The cooling system follows the path : Left radiator (ambient cooled) -> right radiator (ambient air and a fan operating) -> pump -> engine -> reserve tank -> left radiator ect…
My model can be found through the drive : https://drive.google.com/drive/folders/1V4-4UYZZNaCwbORp9fOJHBTNA97NV8K8?usp=sharing
For now, it has been assumed that the engine temperature is constant at 383.15K. I have neglected the effects of the fan, as they operate only when the car is at low speed. The heat exchanger now receives moist air as coolant (so ambient air), and through a pressure source (which I guess is the pressure agains the radiator as the car is driving). The cooling curve looks better, however, as I vary the pressure source value, the coolant temperature doesn’t vary (or I can’t notice on the graph any change in temperature. (it always look like that)
Could anyone help me on that ? Not only the model displays wrong values (from testing, the coolant temperature should sit at 80°C ), but i am also looking for a way to chnaghe the pressure block source, to a volume flow rate in the radiators.
Here is a picture of my updated simplified model. To model the radiators, I have used the tutorial: from mathwork https://uk.mathworks.com/help/hydro/ug/modeling-heat-exchangers.htmHey guys !
I am part of a formula student team, and decided to create a simulation and modelling department for the team, which aims to model our car in Simulink. I am pretty new to simulink/simscape, and as a first task, I wanted to model the car cooling system. The aim is to determine a required flow rates in the radiators to help the aero team to design side pods.
The cooling system follows the path : Left radiator (ambient cooled) -> right radiator (ambient air and a fan operating) -> pump -> engine -> reserve tank -> left radiator ect…
My model can be found through the drive : https://drive.google.com/drive/folders/1V4-4UYZZNaCwbORp9fOJHBTNA97NV8K8?usp=sharing
For now, it has been assumed that the engine temperature is constant at 383.15K. I have neglected the effects of the fan, as they operate only when the car is at low speed. The heat exchanger now receives moist air as coolant (so ambient air), and through a pressure source (which I guess is the pressure agains the radiator as the car is driving). The cooling curve looks better, however, as I vary the pressure source value, the coolant temperature doesn’t vary (or I can’t notice on the graph any change in temperature. (it always look like that)
Could anyone help me on that ? Not only the model displays wrong values (from testing, the coolant temperature should sit at 80°C ), but i am also looking for a way to chnaghe the pressure block source, to a volume flow rate in the radiators.
Here is a picture of my updated simplified model. To model the radiators, I have used the tutorial: from mathwork https://uk.mathworks.com/help/hydro/ug/modeling-heat-exchangers.htm Hey guys !
I am part of a formula student team, and decided to create a simulation and modelling department for the team, which aims to model our car in Simulink. I am pretty new to simulink/simscape, and as a first task, I wanted to model the car cooling system. The aim is to determine a required flow rates in the radiators to help the aero team to design side pods.
The cooling system follows the path : Left radiator (ambient cooled) -> right radiator (ambient air and a fan operating) -> pump -> engine -> reserve tank -> left radiator ect…
My model can be found through the drive : https://drive.google.com/drive/folders/1V4-4UYZZNaCwbORp9fOJHBTNA97NV8K8?usp=sharing
For now, it has been assumed that the engine temperature is constant at 383.15K. I have neglected the effects of the fan, as they operate only when the car is at low speed. The heat exchanger now receives moist air as coolant (so ambient air), and through a pressure source (which I guess is the pressure agains the radiator as the car is driving). The cooling curve looks better, however, as I vary the pressure source value, the coolant temperature doesn’t vary (or I can’t notice on the graph any change in temperature. (it always look like that)
Could anyone help me on that ? Not only the model displays wrong values (from testing, the coolant temperature should sit at 80°C ), but i am also looking for a way to chnaghe the pressure block source, to a volume flow rate in the radiators.
Here is a picture of my updated simplified model. To model the radiators, I have used the tutorial: from mathwork https://uk.mathworks.com/help/hydro/ug/modeling-heat-exchangers.htm fsae, simscape, thermal liquid library, engine cooling MATLAB Answers — New Questions
blank matlab icon on taskbar after a change in matlab directory.
The original matlab directory is c:matlabr2023 and r2023 was moved to c: to replace c:matlab and renamed as matlab r2023. Matlab still works properly except that the matlab icon on the taskbar becomes blank. How to change this icon to the original matlab icon?The original matlab directory is c:matlabr2023 and r2023 was moved to c: to replace c:matlab and renamed as matlab r2023. Matlab still works properly except that the matlab icon on the taskbar becomes blank. How to change this icon to the original matlab icon? The original matlab directory is c:matlabr2023 and r2023 was moved to c: to replace c:matlab and renamed as matlab r2023. Matlab still works properly except that the matlab icon on the taskbar becomes blank. How to change this icon to the original matlab icon? installation MATLAB Answers — New Questions
get error runing TrainTD3AgentForPMSMControlExample.mlx
win10 matlabR2024a
try to run TrainTD3AgentForPMSMControlExample.mlx example
only change :
106 doTraining = true; %false;
i’m trying to train the agent again.
got error:
错误使用 rl.internal.train.OffPolicyTrainer/run_internal_/nestedRunEpisode (第 284 行)
‘mcb_pmsm_foc_sim_RL/Current Control/Input Scaling/ Calculate Position and Speed/Speed Measurement’ 中出错: 无法计算封装初始化命令。
出错 rl.internal.train.OffPolicyTrainer/run_internal_ (第 351 行)
out = nestedRunEpisode(policy);
出错 rl.internal.train.OffPolicyTrainer/run_ (第 40 行)
result = run_internal_(this);
出错 rl.internal.train.Trainer/run (第 8 行)
result = run_(this);
出错 rl.internal.trainmgr.OnlineTrainingManager/run_ (第 112 行)
trainResult = run(trainer);
出错 rl.internal.trainmgr.TrainingManager/run (第 4 行)
result = run_(this);
出错 rl.agent.AbstractAgent/train (第 86 行)
trainingResult = run(tm);
原因:
错误使用 rl.env.internal.reportSimulinkSimError (第 29 行)
在仿真运行时,无法更改 ‘mcb_pmsm_foc_sim_RL/Current Control/Input Scaling/ Calculate Position and Speed/Speed Measurement’ 的属性 ‘Enabled’win10 matlabR2024a
try to run TrainTD3AgentForPMSMControlExample.mlx example
only change :
106 doTraining = true; %false;
i’m trying to train the agent again.
got error:
错误使用 rl.internal.train.OffPolicyTrainer/run_internal_/nestedRunEpisode (第 284 行)
‘mcb_pmsm_foc_sim_RL/Current Control/Input Scaling/ Calculate Position and Speed/Speed Measurement’ 中出错: 无法计算封装初始化命令。
出错 rl.internal.train.OffPolicyTrainer/run_internal_ (第 351 行)
out = nestedRunEpisode(policy);
出错 rl.internal.train.OffPolicyTrainer/run_ (第 40 行)
result = run_internal_(this);
出错 rl.internal.train.Trainer/run (第 8 行)
result = run_(this);
出错 rl.internal.trainmgr.OnlineTrainingManager/run_ (第 112 行)
trainResult = run(trainer);
出错 rl.internal.trainmgr.TrainingManager/run (第 4 行)
result = run_(this);
出错 rl.agent.AbstractAgent/train (第 86 行)
trainingResult = run(tm);
原因:
错误使用 rl.env.internal.reportSimulinkSimError (第 29 行)
在仿真运行时,无法更改 ‘mcb_pmsm_foc_sim_RL/Current Control/Input Scaling/ Calculate Position and Speed/Speed Measurement’ 的属性 ‘Enabled’ win10 matlabR2024a
try to run TrainTD3AgentForPMSMControlExample.mlx example
only change :
106 doTraining = true; %false;
i’m trying to train the agent again.
got error:
错误使用 rl.internal.train.OffPolicyTrainer/run_internal_/nestedRunEpisode (第 284 行)
‘mcb_pmsm_foc_sim_RL/Current Control/Input Scaling/ Calculate Position and Speed/Speed Measurement’ 中出错: 无法计算封装初始化命令。
出错 rl.internal.train.OffPolicyTrainer/run_internal_ (第 351 行)
out = nestedRunEpisode(policy);
出错 rl.internal.train.OffPolicyTrainer/run_ (第 40 行)
result = run_internal_(this);
出错 rl.internal.train.Trainer/run (第 8 行)
result = run_(this);
出错 rl.internal.trainmgr.OnlineTrainingManager/run_ (第 112 行)
trainResult = run(trainer);
出错 rl.internal.trainmgr.TrainingManager/run (第 4 行)
result = run_(this);
出错 rl.agent.AbstractAgent/train (第 86 行)
trainingResult = run(tm);
原因:
错误使用 rl.env.internal.reportSimulinkSimError (第 29 行)
在仿真运行时,无法更改 ‘mcb_pmsm_foc_sim_RL/Current Control/Input Scaling/ Calculate Position and Speed/Speed Measurement’ 的属性 ‘Enabled’ example error MATLAB Answers — New Questions
how to plot the data over an image of graph to validate the data?
I want to plot the data that i got from my simulation over this graph to validate it. I want to know how to do it?I want to plot the data that i got from my simulation over this graph to validate it. I want to know how to do it? I want to plot the data that i got from my simulation over this graph to validate it. I want to know how to do it? plotting over the image MATLAB Answers — New Questions
JSON format from the API
Hello, I’m going to fetch data from the OpenWeatherMap website as an app designer. The API will be in JSON format, but I keep getting errors. Can you help?Hello, I’m going to fetch data from the OpenWeatherMap website as an app designer. The API will be in JSON format, but I keep getting errors. Can you help? Hello, I’m going to fetch data from the OpenWeatherMap website as an app designer. The API will be in JSON format, but I keep getting errors. Can you help? appdesigner, app designer, api, json MATLAB Answers — New Questions
newton law of cooling
The rate at which a hot body loses heat is directly proportional to the difference between the temperature of the hot body and that of its surroundings and depends on the nature of the material and surface area of the body. Suppose m is the mass of a hot body and s is the specific heat at its initial temperature Q higher than its surroundings temperature Qo , dQ/dt is the rate of loss of heat dQ is the amount of heat lost by the hot body to its surroundings in a small interval of time.
1. Develop the differential equation of the hot body losing heat.
2. Enter the differential equation in MATLAB.
3. Solve the differential equation using MATLAB codes.
4. Plot the graph of log_10(Q – Qo) versus t using MATLAB. Then, interpret the results from the drawn graph.
5. Plot the graph of temperature (Q – Qo) versus time t using MATLAB. Interpret the results from the drawn figure.
6. Extract the MATLAB codes and figures for grading.The rate at which a hot body loses heat is directly proportional to the difference between the temperature of the hot body and that of its surroundings and depends on the nature of the material and surface area of the body. Suppose m is the mass of a hot body and s is the specific heat at its initial temperature Q higher than its surroundings temperature Qo , dQ/dt is the rate of loss of heat dQ is the amount of heat lost by the hot body to its surroundings in a small interval of time.
1. Develop the differential equation of the hot body losing heat.
2. Enter the differential equation in MATLAB.
3. Solve the differential equation using MATLAB codes.
4. Plot the graph of log_10(Q – Qo) versus t using MATLAB. Then, interpret the results from the drawn graph.
5. Plot the graph of temperature (Q – Qo) versus time t using MATLAB. Interpret the results from the drawn figure.
6. Extract the MATLAB codes and figures for grading. The rate at which a hot body loses heat is directly proportional to the difference between the temperature of the hot body and that of its surroundings and depends on the nature of the material and surface area of the body. Suppose m is the mass of a hot body and s is the specific heat at its initial temperature Q higher than its surroundings temperature Qo , dQ/dt is the rate of loss of heat dQ is the amount of heat lost by the hot body to its surroundings in a small interval of time.
1. Develop the differential equation of the hot body losing heat.
2. Enter the differential equation in MATLAB.
3. Solve the differential equation using MATLAB codes.
4. Plot the graph of log_10(Q – Qo) versus t using MATLAB. Then, interpret the results from the drawn graph.
5. Plot the graph of temperature (Q – Qo) versus time t using MATLAB. Interpret the results from the drawn figure.
6. Extract the MATLAB codes and figures for grading. differential equation MATLAB Answers — New Questions
findging eigenvectors with eigenvalues
clc; clear;
% Given matrix A
A = [3.6574, -1.9723, 0, 0.8581, 3.0865;
0.5177, 1.4469, 0, 1.1376, -3.7955;
-0.7951, 0.1142, 0.7290, -0.5829, -0.2565;
-0.7273, 2.1819, 0, 2.2816, -6.5275;
0.4301, -1.2904, 0, -0.8602, 3.5590];
% Convergence criterion
tol = 1e-5;
% Number of eigenvalues to find
num_eigenvalues = 3;
% Allocate space for eigenvalues and eigenvectors
eigenvalues = zeros(num_eigenvalues, 1);
eigenvectors = zeros(size(A, 1), num_eigenvalues);
% Function to compute eigenvalues and eigenvectors using inverse iteration and deflation
function [lambda, v] = inverse_iteration(A, x0, tol, max_iter)
v = x0 / norm(x0); % Normalize initial vector
I = eye(size(A));
for k = 1:max_iter
w = (A – I) v; % Solve linear system
v_new = w / norm(w); % Normalize new vector
lambda = v_new’ * A * v_new; % Estimate eigenvalue
if norm(v_new – v, inf) < tol % Check for convergence
v = v_new;
return;
end
v = v_new;
end
end
% Initial guess for eigenvector
x0 = [1; 0; 0; 0; 0];
% Find the three smallest eigenvalues and eigenvectors using inverse iteration and deflation
for i = 1:num_eigenvalues
[lambda, v] = inverse_iteration(A, x0, tol, 1000);
eigenvalues(i) = lambda;
eigenvectors(:, i) = v;
% Deflation step
A = A – lambda * (v * v’);
% Restart with a new initial vector
x0 = rand(size(A, 1), 1);
end
% Display results
disp(‘Eigenvalues:’);
disp(eigenvalues);
disp(‘Eigenvectors:’);
disp(eigenvectors);
This question is about finding 3 smallest eigenvalues and corresponding eigenvectors. If I run this code eigenvlaues work well but each of eigenvalue’s eigenvector comes out wrong could someone modify my code do it can work well?
1. Use the inverse iteration and deflation to find three smallest (in magnitude) eigenvalues and corresponding eigenvectors of the following matrix. Start with an initial eigenvector of (1, 0, 0, 0, 0)T for the power method, and use ∥x(k+1) − x(k)∥∞ ≤ 10−5 as a stopping criteria for your iteration. Approximate the eigenvalues using the Rayleigh Quotient.clc; clear;
% Given matrix A
A = [3.6574, -1.9723, 0, 0.8581, 3.0865;
0.5177, 1.4469, 0, 1.1376, -3.7955;
-0.7951, 0.1142, 0.7290, -0.5829, -0.2565;
-0.7273, 2.1819, 0, 2.2816, -6.5275;
0.4301, -1.2904, 0, -0.8602, 3.5590];
% Convergence criterion
tol = 1e-5;
% Number of eigenvalues to find
num_eigenvalues = 3;
% Allocate space for eigenvalues and eigenvectors
eigenvalues = zeros(num_eigenvalues, 1);
eigenvectors = zeros(size(A, 1), num_eigenvalues);
% Function to compute eigenvalues and eigenvectors using inverse iteration and deflation
function [lambda, v] = inverse_iteration(A, x0, tol, max_iter)
v = x0 / norm(x0); % Normalize initial vector
I = eye(size(A));
for k = 1:max_iter
w = (A – I) v; % Solve linear system
v_new = w / norm(w); % Normalize new vector
lambda = v_new’ * A * v_new; % Estimate eigenvalue
if norm(v_new – v, inf) < tol % Check for convergence
v = v_new;
return;
end
v = v_new;
end
end
% Initial guess for eigenvector
x0 = [1; 0; 0; 0; 0];
% Find the three smallest eigenvalues and eigenvectors using inverse iteration and deflation
for i = 1:num_eigenvalues
[lambda, v] = inverse_iteration(A, x0, tol, 1000);
eigenvalues(i) = lambda;
eigenvectors(:, i) = v;
% Deflation step
A = A – lambda * (v * v’);
% Restart with a new initial vector
x0 = rand(size(A, 1), 1);
end
% Display results
disp(‘Eigenvalues:’);
disp(eigenvalues);
disp(‘Eigenvectors:’);
disp(eigenvectors);
This question is about finding 3 smallest eigenvalues and corresponding eigenvectors. If I run this code eigenvlaues work well but each of eigenvalue’s eigenvector comes out wrong could someone modify my code do it can work well?
1. Use the inverse iteration and deflation to find three smallest (in magnitude) eigenvalues and corresponding eigenvectors of the following matrix. Start with an initial eigenvector of (1, 0, 0, 0, 0)T for the power method, and use ∥x(k+1) − x(k)∥∞ ≤ 10−5 as a stopping criteria for your iteration. Approximate the eigenvalues using the Rayleigh Quotient. clc; clear;
% Given matrix A
A = [3.6574, -1.9723, 0, 0.8581, 3.0865;
0.5177, 1.4469, 0, 1.1376, -3.7955;
-0.7951, 0.1142, 0.7290, -0.5829, -0.2565;
-0.7273, 2.1819, 0, 2.2816, -6.5275;
0.4301, -1.2904, 0, -0.8602, 3.5590];
% Convergence criterion
tol = 1e-5;
% Number of eigenvalues to find
num_eigenvalues = 3;
% Allocate space for eigenvalues and eigenvectors
eigenvalues = zeros(num_eigenvalues, 1);
eigenvectors = zeros(size(A, 1), num_eigenvalues);
% Function to compute eigenvalues and eigenvectors using inverse iteration and deflation
function [lambda, v] = inverse_iteration(A, x0, tol, max_iter)
v = x0 / norm(x0); % Normalize initial vector
I = eye(size(A));
for k = 1:max_iter
w = (A – I) v; % Solve linear system
v_new = w / norm(w); % Normalize new vector
lambda = v_new’ * A * v_new; % Estimate eigenvalue
if norm(v_new – v, inf) < tol % Check for convergence
v = v_new;
return;
end
v = v_new;
end
end
% Initial guess for eigenvector
x0 = [1; 0; 0; 0; 0];
% Find the three smallest eigenvalues and eigenvectors using inverse iteration and deflation
for i = 1:num_eigenvalues
[lambda, v] = inverse_iteration(A, x0, tol, 1000);
eigenvalues(i) = lambda;
eigenvectors(:, i) = v;
% Deflation step
A = A – lambda * (v * v’);
% Restart with a new initial vector
x0 = rand(size(A, 1), 1);
end
% Display results
disp(‘Eigenvalues:’);
disp(eigenvalues);
disp(‘Eigenvectors:’);
disp(eigenvectors);
This question is about finding 3 smallest eigenvalues and corresponding eigenvectors. If I run this code eigenvlaues work well but each of eigenvalue’s eigenvector comes out wrong could someone modify my code do it can work well?
1. Use the inverse iteration and deflation to find three smallest (in magnitude) eigenvalues and corresponding eigenvectors of the following matrix. Start with an initial eigenvector of (1, 0, 0, 0, 0)T for the power method, and use ∥x(k+1) − x(k)∥∞ ≤ 10−5 as a stopping criteria for your iteration. Approximate the eigenvalues using the Rayleigh Quotient. eigenvalue eigenvector, rayleigh quotient, inverse iteration, deflation MATLAB Answers — New Questions
EEG lab pop_spectopo()
Hi,
I would like to plot the power spectra of my events in EEGlab which were labelled by EDF browser.
The pop_spectopo() does the whole EEG epoch.
I cant seem to be finding the code to slectively do this for certain event types with a specified time from the event annotation.
Could anyone help me with this. I had trimmed the original EDF file to select data by events only.Hi,
I would like to plot the power spectra of my events in EEGlab which were labelled by EDF browser.
The pop_spectopo() does the whole EEG epoch.
I cant seem to be finding the code to slectively do this for certain event types with a specified time from the event annotation.
Could anyone help me with this. I had trimmed the original EDF file to select data by events only. Hi,
I would like to plot the power spectra of my events in EEGlab which were labelled by EDF browser.
The pop_spectopo() does the whole EEG epoch.
I cant seem to be finding the code to slectively do this for certain event types with a specified time from the event annotation.
Could anyone help me with this. I had trimmed the original EDF file to select data by events only. eeglab, powerspectra MATLAB Answers — New Questions
Is the “margin(sys)” code correct in online and offline Matlab software?
I could not get the gain cross over frequency, phase crossover frequency, gain margin, phase margin correctly using the "margin(sys)" command.I could not get the gain cross over frequency, phase crossover frequency, gain margin, phase margin correctly using the "margin(sys)" command. I could not get the gain cross over frequency, phase crossover frequency, gain margin, phase margin correctly using the "margin(sys)" command. transferred MATLAB Answers — New Questions
How to find the MADB h based on LMI?
A=[-2,0;0,-0.9];
B=[-1,0;-1,-1];
D=[-0.2;-0.3];
M=[0.3,0.1];
N=[0.1,0.2];
G=[0.1,0;0,0.1];
Ed=[0;0];
Ea=[1,0;0,1];
Eb=[1,0;0,1];
K1=0.2;
K2=0.5;
hd=9;
setlmis([]);
Q1=lmivar(1,[2,1]);
Z1=lmivar(1,[2,1]);
Q2=lmivar(1,[2,1]);
Z2=lmivar(1,[2,1]);
Q1=lmivar(1,[2,1]);
P=lmivar(1,[2,1]);
I=lmivar(1,[2,1]);
epi=lmivar(1, [1,0]);
miu=lmivar(1, [1,0]);
h=lmivar(1, [1,0]);
lmiterm([1,1,1,P],A’,1);
lmiterm([1,1,1,P],1,A);
lmiterm([1,1,1,P],1,-D*K1*M);
lmiterm([1,1,1,P],-M’*K1’*D’,1);
lmiterm([1,1,1,-Z1],-1,1);
lmiterm([1,1,1,Q2],1,1);
lmiterm([1,1,2,Z1],1,1);
lmiterm([1,1,3,P],1,B);
lmiterm([1,1,3,P],-1,D*K1*N);
lmiterm([1,1,4,P],1,D);
lmiterm([1,1,4,epi],1,-M’*K2′);
lmiterm([1,1,4,epi],1,M’*K1′);
lmiterm([1,1,5,Z1],(h/2)*A’,1);
lmiterm([1,1,5,Z2],(h/2)*A’,1);
lmiterm([1,1,5,Z1],-M’*K1’*D’,1);
lmiterm([1,1,5,Z2],-M’*K1’*D’,1);
lmiterm([1,1,6,P],G’,1);
lmiterm([1,1,7,miu],1,Ea);
lmiterm([1,1,7,miu],1,-Ed*K1*M);
lmiterm([1,2,2,Z1],-1,1);
lmiterm([1,2,2,Z2],-1,1);
lmiterm([1,2,2,Q1],1,1);
lmiterm([1,2,2,Q2],-1,1);
lmiterm([1,2,3,Z2],1,1);
lmiterm([1,3,3,Z2],-1,1);
lmiterm([1,3,3,Q1],-1,1);
lmiterm([1,3,4,epi],1,-N’*K2′);
lmiterm([1,3,4,epi],1,N’*K1′);
lmiterm([1,3,5,Z1],(h/2)*B’,1);
lmiterm([1,3,5,Z2],(h/2)*B’,1);
lmiterm([1,3,5,Z1],-N’*K1’*D’,1);
lmiterm([1,3,5,Z2],-N’*K1’*D’,1);
lmiterm([1,3,7,miu],1,Eb);
lmiterm([1,3,7,miu],1,-Ed*K1*N);
lmiterm([1,4,4,0],-1);
lmiterm([1,4,5,Z1],(h/2)*D’,1);
lmiterm([1,4,5,Z2],(h/2)*D’,1);
lmiterm([1,4,7,miu],1,Ed);
lmiterm([1,5,5,Z1],-1,1);
lmiterm([1,5,5,Z2],-1,1);
lmiterm([1,5,6,Z1],(h/2)*G’,1);
lmiterm([1,5,6,Z2],(h/2)*G’,1);
lmiterm([1,6,6,0],-1);
lmiterm([1,7,7,0],-1);
lmiterm([-2,1,1,Q1],1,1);
lmiterm([-3,1,1,Z1],1,1);
lmiterm([-4,1,1,Q2],1,1);
lmiterm([-5,1,1,Z2],1,1);
lmiterm([-6,1,1,P],1,1);
lmiterm([-7,1,1,epi],1,1);
lmiterm([-8,1,1,miu],1,1);
lmiterm([-9,1,1,h],1,1);
lmisys=getlmis;
[tmin, xfeas] =feasp(lmisys) ;
if(tmin<0)
string=[‘tmin= ‘,num2str(tmin)];
disp(string)
options=[1e-5, 0, 0, 0, 0];
c=mat2dec(lmisys, eye(1,1) ) ;
[copt,xopt]=mincx(lmisys , c, options);
-h==dec2mat(lmisys, xopt, -h);
endA=[-2,0;0,-0.9];
B=[-1,0;-1,-1];
D=[-0.2;-0.3];
M=[0.3,0.1];
N=[0.1,0.2];
G=[0.1,0;0,0.1];
Ed=[0;0];
Ea=[1,0;0,1];
Eb=[1,0;0,1];
K1=0.2;
K2=0.5;
hd=9;
setlmis([]);
Q1=lmivar(1,[2,1]);
Z1=lmivar(1,[2,1]);
Q2=lmivar(1,[2,1]);
Z2=lmivar(1,[2,1]);
Q1=lmivar(1,[2,1]);
P=lmivar(1,[2,1]);
I=lmivar(1,[2,1]);
epi=lmivar(1, [1,0]);
miu=lmivar(1, [1,0]);
h=lmivar(1, [1,0]);
lmiterm([1,1,1,P],A’,1);
lmiterm([1,1,1,P],1,A);
lmiterm([1,1,1,P],1,-D*K1*M);
lmiterm([1,1,1,P],-M’*K1’*D’,1);
lmiterm([1,1,1,-Z1],-1,1);
lmiterm([1,1,1,Q2],1,1);
lmiterm([1,1,2,Z1],1,1);
lmiterm([1,1,3,P],1,B);
lmiterm([1,1,3,P],-1,D*K1*N);
lmiterm([1,1,4,P],1,D);
lmiterm([1,1,4,epi],1,-M’*K2′);
lmiterm([1,1,4,epi],1,M’*K1′);
lmiterm([1,1,5,Z1],(h/2)*A’,1);
lmiterm([1,1,5,Z2],(h/2)*A’,1);
lmiterm([1,1,5,Z1],-M’*K1’*D’,1);
lmiterm([1,1,5,Z2],-M’*K1’*D’,1);
lmiterm([1,1,6,P],G’,1);
lmiterm([1,1,7,miu],1,Ea);
lmiterm([1,1,7,miu],1,-Ed*K1*M);
lmiterm([1,2,2,Z1],-1,1);
lmiterm([1,2,2,Z2],-1,1);
lmiterm([1,2,2,Q1],1,1);
lmiterm([1,2,2,Q2],-1,1);
lmiterm([1,2,3,Z2],1,1);
lmiterm([1,3,3,Z2],-1,1);
lmiterm([1,3,3,Q1],-1,1);
lmiterm([1,3,4,epi],1,-N’*K2′);
lmiterm([1,3,4,epi],1,N’*K1′);
lmiterm([1,3,5,Z1],(h/2)*B’,1);
lmiterm([1,3,5,Z2],(h/2)*B’,1);
lmiterm([1,3,5,Z1],-N’*K1’*D’,1);
lmiterm([1,3,5,Z2],-N’*K1’*D’,1);
lmiterm([1,3,7,miu],1,Eb);
lmiterm([1,3,7,miu],1,-Ed*K1*N);
lmiterm([1,4,4,0],-1);
lmiterm([1,4,5,Z1],(h/2)*D’,1);
lmiterm([1,4,5,Z2],(h/2)*D’,1);
lmiterm([1,4,7,miu],1,Ed);
lmiterm([1,5,5,Z1],-1,1);
lmiterm([1,5,5,Z2],-1,1);
lmiterm([1,5,6,Z1],(h/2)*G’,1);
lmiterm([1,5,6,Z2],(h/2)*G’,1);
lmiterm([1,6,6,0],-1);
lmiterm([1,7,7,0],-1);
lmiterm([-2,1,1,Q1],1,1);
lmiterm([-3,1,1,Z1],1,1);
lmiterm([-4,1,1,Q2],1,1);
lmiterm([-5,1,1,Z2],1,1);
lmiterm([-6,1,1,P],1,1);
lmiterm([-7,1,1,epi],1,1);
lmiterm([-8,1,1,miu],1,1);
lmiterm([-9,1,1,h],1,1);
lmisys=getlmis;
[tmin, xfeas] =feasp(lmisys) ;
if(tmin<0)
string=[‘tmin= ‘,num2str(tmin)];
disp(string)
options=[1e-5, 0, 0, 0, 0];
c=mat2dec(lmisys, eye(1,1) ) ;
[copt,xopt]=mincx(lmisys , c, options);
-h==dec2mat(lmisys, xopt, -h);
end A=[-2,0;0,-0.9];
B=[-1,0;-1,-1];
D=[-0.2;-0.3];
M=[0.3,0.1];
N=[0.1,0.2];
G=[0.1,0;0,0.1];
Ed=[0;0];
Ea=[1,0;0,1];
Eb=[1,0;0,1];
K1=0.2;
K2=0.5;
hd=9;
setlmis([]);
Q1=lmivar(1,[2,1]);
Z1=lmivar(1,[2,1]);
Q2=lmivar(1,[2,1]);
Z2=lmivar(1,[2,1]);
Q1=lmivar(1,[2,1]);
P=lmivar(1,[2,1]);
I=lmivar(1,[2,1]);
epi=lmivar(1, [1,0]);
miu=lmivar(1, [1,0]);
h=lmivar(1, [1,0]);
lmiterm([1,1,1,P],A’,1);
lmiterm([1,1,1,P],1,A);
lmiterm([1,1,1,P],1,-D*K1*M);
lmiterm([1,1,1,P],-M’*K1’*D’,1);
lmiterm([1,1,1,-Z1],-1,1);
lmiterm([1,1,1,Q2],1,1);
lmiterm([1,1,2,Z1],1,1);
lmiterm([1,1,3,P],1,B);
lmiterm([1,1,3,P],-1,D*K1*N);
lmiterm([1,1,4,P],1,D);
lmiterm([1,1,4,epi],1,-M’*K2′);
lmiterm([1,1,4,epi],1,M’*K1′);
lmiterm([1,1,5,Z1],(h/2)*A’,1);
lmiterm([1,1,5,Z2],(h/2)*A’,1);
lmiterm([1,1,5,Z1],-M’*K1’*D’,1);
lmiterm([1,1,5,Z2],-M’*K1’*D’,1);
lmiterm([1,1,6,P],G’,1);
lmiterm([1,1,7,miu],1,Ea);
lmiterm([1,1,7,miu],1,-Ed*K1*M);
lmiterm([1,2,2,Z1],-1,1);
lmiterm([1,2,2,Z2],-1,1);
lmiterm([1,2,2,Q1],1,1);
lmiterm([1,2,2,Q2],-1,1);
lmiterm([1,2,3,Z2],1,1);
lmiterm([1,3,3,Z2],-1,1);
lmiterm([1,3,3,Q1],-1,1);
lmiterm([1,3,4,epi],1,-N’*K2′);
lmiterm([1,3,4,epi],1,N’*K1′);
lmiterm([1,3,5,Z1],(h/2)*B’,1);
lmiterm([1,3,5,Z2],(h/2)*B’,1);
lmiterm([1,3,5,Z1],-N’*K1’*D’,1);
lmiterm([1,3,5,Z2],-N’*K1’*D’,1);
lmiterm([1,3,7,miu],1,Eb);
lmiterm([1,3,7,miu],1,-Ed*K1*N);
lmiterm([1,4,4,0],-1);
lmiterm([1,4,5,Z1],(h/2)*D’,1);
lmiterm([1,4,5,Z2],(h/2)*D’,1);
lmiterm([1,4,7,miu],1,Ed);
lmiterm([1,5,5,Z1],-1,1);
lmiterm([1,5,5,Z2],-1,1);
lmiterm([1,5,6,Z1],(h/2)*G’,1);
lmiterm([1,5,6,Z2],(h/2)*G’,1);
lmiterm([1,6,6,0],-1);
lmiterm([1,7,7,0],-1);
lmiterm([-2,1,1,Q1],1,1);
lmiterm([-3,1,1,Z1],1,1);
lmiterm([-4,1,1,Q2],1,1);
lmiterm([-5,1,1,Z2],1,1);
lmiterm([-6,1,1,P],1,1);
lmiterm([-7,1,1,epi],1,1);
lmiterm([-8,1,1,miu],1,1);
lmiterm([-9,1,1,h],1,1);
lmisys=getlmis;
[tmin, xfeas] =feasp(lmisys) ;
if(tmin<0)
string=[‘tmin= ‘,num2str(tmin)];
disp(string)
options=[1e-5, 0, 0, 0, 0];
c=mat2dec(lmisys, eye(1,1) ) ;
[copt,xopt]=mincx(lmisys , c, options);
-h==dec2mat(lmisys, xopt, -h);
end lmi, optimization MATLAB Answers — New Questions
Reading in .txt File
Hello, I have a text file I’d like to read in. Here is aforementioned text file (text_a2p.txt):
object index_image.nii
plane transverse
range 100 150
factor 3.1415926535897
coeff .0001 .0004 -.0006
As you can see, it’s not vertically oriented like most tables (honestly I wouldn’t even really call it a table). It also contains both strings and doubles in varying amounts, which throws pretty much every method I’ve tried completely off-kilter.
The word that begins each line specifies what comes after it (ex. the last line contains the coefficients for a polynomial fit generated by the code). Those specifying words don’t actually count as data, and won’t end up being processed, they just help to clarify. They could serve as the names of the variables the data is stored in, however.
Unfortunately, the general format of the text file is fixed. It is also worth mentioning that ‘plane’ will always only have one string after it, and ‘factor’ will always have one number after it, but there could be any number of objects, range pairs, and coefficients. So, the text file could also look like this.
object index_image.nii map1_image.nii map2_image.nii
plane sagittal
range 100 150 200 250
factor 2.7182818284590
coeff 3 1 4 1 5 9
How do I import this text file and neatly separate it so that I can isolate each variable? Ideally, I’d have a few arrays (or cells, or whatever is most convenient) that look like this.
object = ["index_image.nii", "map1_image.nii", "map2_image.nii"];
plane = ["saggital"];
range = [100, 150, 200, 250];
factor = 2.17182818284590;
coeff = [3, 1, 4, 1, 5, 9];
The variables don’t have to be named any particular way, I’m more just focused on the issue of extracting them. Thank you!Hello, I have a text file I’d like to read in. Here is aforementioned text file (text_a2p.txt):
object index_image.nii
plane transverse
range 100 150
factor 3.1415926535897
coeff .0001 .0004 -.0006
As you can see, it’s not vertically oriented like most tables (honestly I wouldn’t even really call it a table). It also contains both strings and doubles in varying amounts, which throws pretty much every method I’ve tried completely off-kilter.
The word that begins each line specifies what comes after it (ex. the last line contains the coefficients for a polynomial fit generated by the code). Those specifying words don’t actually count as data, and won’t end up being processed, they just help to clarify. They could serve as the names of the variables the data is stored in, however.
Unfortunately, the general format of the text file is fixed. It is also worth mentioning that ‘plane’ will always only have one string after it, and ‘factor’ will always have one number after it, but there could be any number of objects, range pairs, and coefficients. So, the text file could also look like this.
object index_image.nii map1_image.nii map2_image.nii
plane sagittal
range 100 150 200 250
factor 2.7182818284590
coeff 3 1 4 1 5 9
How do I import this text file and neatly separate it so that I can isolate each variable? Ideally, I’d have a few arrays (or cells, or whatever is most convenient) that look like this.
object = ["index_image.nii", "map1_image.nii", "map2_image.nii"];
plane = ["saggital"];
range = [100, 150, 200, 250];
factor = 2.17182818284590;
coeff = [3, 1, 4, 1, 5, 9];
The variables don’t have to be named any particular way, I’m more just focused on the issue of extracting them. Thank you! Hello, I have a text file I’d like to read in. Here is aforementioned text file (text_a2p.txt):
object index_image.nii
plane transverse
range 100 150
factor 3.1415926535897
coeff .0001 .0004 -.0006
As you can see, it’s not vertically oriented like most tables (honestly I wouldn’t even really call it a table). It also contains both strings and doubles in varying amounts, which throws pretty much every method I’ve tried completely off-kilter.
The word that begins each line specifies what comes after it (ex. the last line contains the coefficients for a polynomial fit generated by the code). Those specifying words don’t actually count as data, and won’t end up being processed, they just help to clarify. They could serve as the names of the variables the data is stored in, however.
Unfortunately, the general format of the text file is fixed. It is also worth mentioning that ‘plane’ will always only have one string after it, and ‘factor’ will always have one number after it, but there could be any number of objects, range pairs, and coefficients. So, the text file could also look like this.
object index_image.nii map1_image.nii map2_image.nii
plane sagittal
range 100 150 200 250
factor 2.7182818284590
coeff 3 1 4 1 5 9
How do I import this text file and neatly separate it so that I can isolate each variable? Ideally, I’d have a few arrays (or cells, or whatever is most convenient) that look like this.
object = ["index_image.nii", "map1_image.nii", "map2_image.nii"];
plane = ["saggital"];
range = [100, 150, 200, 250];
factor = 2.17182818284590;
coeff = [3, 1, 4, 1, 5, 9];
The variables don’t have to be named any particular way, I’m more just focused on the issue of extracting them. Thank you! text file, data import MATLAB Answers — New Questions
When model is loaded how does old Variant Model blocks convert to a subsystem variant with model blocks as choices?
When Model Variant has two choices lets say
Model Block1 (Choice1) has inports { ‘In1’, ‘In2’, ‘In3’} , let say this choice is selected
Model Block2 (Choice2) has inports { ‘my_In1’, ‘my_In2’, ‘my_In3’}When Model Variant has two choices lets say
Model Block1 (Choice1) has inports { ‘In1’, ‘In2’, ‘In3’} , let say this choice is selected
Model Block2 (Choice2) has inports { ‘my_In1’, ‘my_In2’, ‘my_In3’} When Model Variant has two choices lets say
Model Block1 (Choice1) has inports { ‘In1’, ‘In2’, ‘In3’} , let say this choice is selected
Model Block2 (Choice2) has inports { ‘my_In1’, ‘my_In2’, ‘my_In3’} variant model MATLAB Answers — New Questions
Como se que metodo esta utilizando Matlab al graficar ltiview?
Hola, buenas tardes
Como puedo saber que metodo esta usando Matlab para el calculo de Rise Time, lo que pasa es que con las formulas de los libros no se aproxima a lo que entrega Matlab.Hola, buenas tardes
Como puedo saber que metodo esta usando Matlab para el calculo de Rise Time, lo que pasa es que con las formulas de los libros no se aproxima a lo que entrega Matlab. Hola, buenas tardes
Como puedo saber que metodo esta usando Matlab para el calculo de Rise Time, lo que pasa es que con las formulas de los libros no se aproxima a lo que entrega Matlab. ltiview, rise_time MATLAB Answers — New Questions
Looking for data structure ideas for App Designer GUI used to set simulation inputs
Hi all,
I’m looking for advice or ideas on how to manage data structures.
I have an App Designer GUI for a user to input data, which is then written to a save file (.mat). This file is loaded into an agent-based Monte Carlo simulation.
The agents used in the simulation are unlimited in number, include multiple agent types, and each instance (for each agent type) stores multiple data classes (e.g., strings, doubles, Booleans, arrays, etc.)
Currently, the data flow in the GUI is: data input field -> Map Container object -> Cell Array in the input GUI.
And, when used by the sim, the data flow is: Cell Array -> Map Container object (in a loop) -> named variable (in a function called in the loop)
For example:
% Numeric input field callback in the data input GUI
app.GreenAgent_InputsMap(‘Var1’) = app.GreenAgent_Var1_InputField.Value;
% Write inputs map to cell array (by index) in the data input GUI, which is then saved to a .mat file
% (without the .app scope)
app.GreenAgent_InputsCells{n} = app.GreenAgent_InputsMap.keys();
app.GreenAgent_InputCells{n+1} = app.GreenAgent_InputsMap.values();
% In the simulation, the .mat file is opened (in a loop)
GreenAgent_InputsMap = containers.Map(GreenAgent_InputCells{n}, GreenAgent_InputCells{n+1});
GreenAgent_Var1 = GreenAgent_InputsMap(‘Var1’);
I use the Map Containers to: 1) use names (like a dictionary) rather than index position in a cell array; and 2) store multiple data types. I use the Cell Arrays to unpack data for each agent type iteratively.
There are too many variables in each agent type to outright name the variables individually, especially considering an unlimited number of each agent type can be created by the user. As is, I’m effectively creating 3 copies of each variable:
The App Designer input field (the input fields switch whenever a different agent of the same type is selected for editing)
The Map Container key/value pair (the Map Container is overwritten whenever a different agent of the same type is selected for editing)
The Cell Array where the data is ultimately stored and used by the sim (to support looping over an unlimited number of agents)
I’m wondering if there is a more elegant solution. For instance, it would be nice if each variable for an agent (i.e., in the Map Container) supported highlighting in the MATLAB editor to quickly find all the instances where that variable (‘Var1’ in the example code) is called and/or overwritten. I’ve thought about using structure arrays to take the place of the Map Containers and Cell Arrays, but that wouldn’t solve the highlighting limitation, and I’m not sure if that is the best approach either.
Thanks for reading to this point!Hi all,
I’m looking for advice or ideas on how to manage data structures.
I have an App Designer GUI for a user to input data, which is then written to a save file (.mat). This file is loaded into an agent-based Monte Carlo simulation.
The agents used in the simulation are unlimited in number, include multiple agent types, and each instance (for each agent type) stores multiple data classes (e.g., strings, doubles, Booleans, arrays, etc.)
Currently, the data flow in the GUI is: data input field -> Map Container object -> Cell Array in the input GUI.
And, when used by the sim, the data flow is: Cell Array -> Map Container object (in a loop) -> named variable (in a function called in the loop)
For example:
% Numeric input field callback in the data input GUI
app.GreenAgent_InputsMap(‘Var1’) = app.GreenAgent_Var1_InputField.Value;
% Write inputs map to cell array (by index) in the data input GUI, which is then saved to a .mat file
% (without the .app scope)
app.GreenAgent_InputsCells{n} = app.GreenAgent_InputsMap.keys();
app.GreenAgent_InputCells{n+1} = app.GreenAgent_InputsMap.values();
% In the simulation, the .mat file is opened (in a loop)
GreenAgent_InputsMap = containers.Map(GreenAgent_InputCells{n}, GreenAgent_InputCells{n+1});
GreenAgent_Var1 = GreenAgent_InputsMap(‘Var1’);
I use the Map Containers to: 1) use names (like a dictionary) rather than index position in a cell array; and 2) store multiple data types. I use the Cell Arrays to unpack data for each agent type iteratively.
There are too many variables in each agent type to outright name the variables individually, especially considering an unlimited number of each agent type can be created by the user. As is, I’m effectively creating 3 copies of each variable:
The App Designer input field (the input fields switch whenever a different agent of the same type is selected for editing)
The Map Container key/value pair (the Map Container is overwritten whenever a different agent of the same type is selected for editing)
The Cell Array where the data is ultimately stored and used by the sim (to support looping over an unlimited number of agents)
I’m wondering if there is a more elegant solution. For instance, it would be nice if each variable for an agent (i.e., in the Map Container) supported highlighting in the MATLAB editor to quickly find all the instances where that variable (‘Var1’ in the example code) is called and/or overwritten. I’ve thought about using structure arrays to take the place of the Map Containers and Cell Arrays, but that wouldn’t solve the highlighting limitation, and I’m not sure if that is the best approach either.
Thanks for reading to this point! Hi all,
I’m looking for advice or ideas on how to manage data structures.
I have an App Designer GUI for a user to input data, which is then written to a save file (.mat). This file is loaded into an agent-based Monte Carlo simulation.
The agents used in the simulation are unlimited in number, include multiple agent types, and each instance (for each agent type) stores multiple data classes (e.g., strings, doubles, Booleans, arrays, etc.)
Currently, the data flow in the GUI is: data input field -> Map Container object -> Cell Array in the input GUI.
And, when used by the sim, the data flow is: Cell Array -> Map Container object (in a loop) -> named variable (in a function called in the loop)
For example:
% Numeric input field callback in the data input GUI
app.GreenAgent_InputsMap(‘Var1’) = app.GreenAgent_Var1_InputField.Value;
% Write inputs map to cell array (by index) in the data input GUI, which is then saved to a .mat file
% (without the .app scope)
app.GreenAgent_InputsCells{n} = app.GreenAgent_InputsMap.keys();
app.GreenAgent_InputCells{n+1} = app.GreenAgent_InputsMap.values();
% In the simulation, the .mat file is opened (in a loop)
GreenAgent_InputsMap = containers.Map(GreenAgent_InputCells{n}, GreenAgent_InputCells{n+1});
GreenAgent_Var1 = GreenAgent_InputsMap(‘Var1’);
I use the Map Containers to: 1) use names (like a dictionary) rather than index position in a cell array; and 2) store multiple data types. I use the Cell Arrays to unpack data for each agent type iteratively.
There are too many variables in each agent type to outright name the variables individually, especially considering an unlimited number of each agent type can be created by the user. As is, I’m effectively creating 3 copies of each variable:
The App Designer input field (the input fields switch whenever a different agent of the same type is selected for editing)
The Map Container key/value pair (the Map Container is overwritten whenever a different agent of the same type is selected for editing)
The Cell Array where the data is ultimately stored and used by the sim (to support looping over an unlimited number of agents)
I’m wondering if there is a more elegant solution. For instance, it would be nice if each variable for an agent (i.e., in the Map Container) supported highlighting in the MATLAB editor to quickly find all the instances where that variable (‘Var1’ in the example code) is called and/or overwritten. I’ve thought about using structure arrays to take the place of the Map Containers and Cell Arrays, but that wouldn’t solve the highlighting limitation, and I’m not sure if that is the best approach either.
Thanks for reading to this point! data structures, map containers, cell arrays, app designer MATLAB Answers — New Questions
How to use SimulinkRealTime.target/getsignal on bus signal?
The documentation for simulink realtime `getsignal` https://www.mathworks.com/help/slrealtime/api/slrealtime.target.getsignal.html says that the output can be a struct if the signal is a bus.
I made a nonvirtual bus signal. See screenshot below.
The signal is not in the list of signals when I use `tg.ShowSignals = ‘on’;` and display `tg`. See attached file output.txt
I have tried attaching a gain block to the bus output. The gain block signal is visible and I can call getsignal on it, but getsignal returns a single double which seems to be the first of the 6 bus elements. I want the all 6 elements of my bus in one struct. (I want to use a bus signal and getsignal the bus signal because calling getsignal 6 times is too slow for the matlab program I am trying to write.)
Thanks in advance for any help.The documentation for simulink realtime `getsignal` https://www.mathworks.com/help/slrealtime/api/slrealtime.target.getsignal.html says that the output can be a struct if the signal is a bus.
I made a nonvirtual bus signal. See screenshot below.
The signal is not in the list of signals when I use `tg.ShowSignals = ‘on’;` and display `tg`. See attached file output.txt
I have tried attaching a gain block to the bus output. The gain block signal is visible and I can call getsignal on it, but getsignal returns a single double which seems to be the first of the 6 bus elements. I want the all 6 elements of my bus in one struct. (I want to use a bus signal and getsignal the bus signal because calling getsignal 6 times is too slow for the matlab program I am trying to write.)
Thanks in advance for any help. The documentation for simulink realtime `getsignal` https://www.mathworks.com/help/slrealtime/api/slrealtime.target.getsignal.html says that the output can be a struct if the signal is a bus.
I made a nonvirtual bus signal. See screenshot below.
The signal is not in the list of signals when I use `tg.ShowSignals = ‘on’;` and display `tg`. See attached file output.txt
I have tried attaching a gain block to the bus output. The gain block signal is visible and I can call getsignal on it, but getsignal returns a single double which seems to be the first of the 6 bus elements. I want the all 6 elements of my bus in one struct. (I want to use a bus signal and getsignal the bus signal because calling getsignal 6 times is too slow for the matlab program I am trying to write.)
Thanks in advance for any help. simulink, matlab MATLAB Answers — New Questions
Plotting of a rolling ball
Hi all,
I have data as below. First column is time column. The second column is x values and the third column is y values. I want to plot this data.The data shows that a round ball is at the x and y location at given time. This ball seems to be shifting/rolling. How can I plot this movement of the ball? The data is as follows.
Thanks.
0 0 0
0.00500000000000000 -1.99184823748972e-07 1.05798917365090e-13
0.0100000000000000 -9.95522559684969e-07 2.64284044491124e-12
0.0150000000000000 -2.70844960991857e-06 1.95618647719148e-11
0.0200000000000000 -5.57897138597691e-06 8.29997912681309e-11
0.0250000000000000 -9.72602113360498e-06 2.52254632243548e-10
0.0300000000000000 -1.52681885391364e-05 6.21646883377640e-10
0.0350000000000000 -2.24451354098218e-05 1.34342427617396e-09
0.0400000000000000 -3.12528324201816e-05 2.60463875809055e-09
0.0450000000000000 -4.14440486717297e-05 4.58029112081254e-09
0.0500000000000000 -5.27718390114465e-05 7.42631198040007e-09
0.0550000000000000 -6.49895772581970e-05 1.12630537391977e-08
0.0600000000000000 -7.79724695483816e-05 1.62125493532621e-08
0.0650000000000000 -9.15958589238721e-05 2.23728036586717e-08
0.0700000000000000 -0.000105613752470057 2.97447058954838e-08
0.0750000000000000 -0.000119902041788388 3.83373323333985e-08Hi all,
I have data as below. First column is time column. The second column is x values and the third column is y values. I want to plot this data.The data shows that a round ball is at the x and y location at given time. This ball seems to be shifting/rolling. How can I plot this movement of the ball? The data is as follows.
Thanks.
0 0 0
0.00500000000000000 -1.99184823748972e-07 1.05798917365090e-13
0.0100000000000000 -9.95522559684969e-07 2.64284044491124e-12
0.0150000000000000 -2.70844960991857e-06 1.95618647719148e-11
0.0200000000000000 -5.57897138597691e-06 8.29997912681309e-11
0.0250000000000000 -9.72602113360498e-06 2.52254632243548e-10
0.0300000000000000 -1.52681885391364e-05 6.21646883377640e-10
0.0350000000000000 -2.24451354098218e-05 1.34342427617396e-09
0.0400000000000000 -3.12528324201816e-05 2.60463875809055e-09
0.0450000000000000 -4.14440486717297e-05 4.58029112081254e-09
0.0500000000000000 -5.27718390114465e-05 7.42631198040007e-09
0.0550000000000000 -6.49895772581970e-05 1.12630537391977e-08
0.0600000000000000 -7.79724695483816e-05 1.62125493532621e-08
0.0650000000000000 -9.15958589238721e-05 2.23728036586717e-08
0.0700000000000000 -0.000105613752470057 2.97447058954838e-08
0.0750000000000000 -0.000119902041788388 3.83373323333985e-08 Hi all,
I have data as below. First column is time column. The second column is x values and the third column is y values. I want to plot this data.The data shows that a round ball is at the x and y location at given time. This ball seems to be shifting/rolling. How can I plot this movement of the ball? The data is as follows.
Thanks.
0 0 0
0.00500000000000000 -1.99184823748972e-07 1.05798917365090e-13
0.0100000000000000 -9.95522559684969e-07 2.64284044491124e-12
0.0150000000000000 -2.70844960991857e-06 1.95618647719148e-11
0.0200000000000000 -5.57897138597691e-06 8.29997912681309e-11
0.0250000000000000 -9.72602113360498e-06 2.52254632243548e-10
0.0300000000000000 -1.52681885391364e-05 6.21646883377640e-10
0.0350000000000000 -2.24451354098218e-05 1.34342427617396e-09
0.0400000000000000 -3.12528324201816e-05 2.60463875809055e-09
0.0450000000000000 -4.14440486717297e-05 4.58029112081254e-09
0.0500000000000000 -5.27718390114465e-05 7.42631198040007e-09
0.0550000000000000 -6.49895772581970e-05 1.12630537391977e-08
0.0600000000000000 -7.79724695483816e-05 1.62125493532621e-08
0.0650000000000000 -9.15958589238721e-05 2.23728036586717e-08
0.0700000000000000 -0.000105613752470057 2.97447058954838e-08
0.0750000000000000 -0.000119902041788388 3.83373323333985e-08 real time plot, plot, rolling ball, time dependent MATLAB Answers — New Questions
Simulink Onramp 13.1 task 2
there seems to be an error while trying to load the constants on matlab what might this be due to?there seems to be an error while trying to load the constants on matlab what might this be due to? there seems to be an error while trying to load the constants on matlab what might this be due to? simulink, onramp MATLAB Answers — New Questions
Input image size must be greater than [64 1856] error in lidar labeler app
I have an error in my machine learning algorithm where it would display an issue with the image size. I am using a .pcd file different to pandaSet yet I am wondering about why theres an error with the network model. I cant seem to determine what creates the netSize and how would I influence it for a new set of pcd dataSet
Error is:
Error using
Input image size must be greater than [64 1856]. The minimum input image size must be equal to or
greater than the input size in image input layer of the network.
Error in ()
iCheckImage(I, netSize);
Error in (line 244)
params = iParseInputs(I, net, varargin{:});
Error in lidar.labeler.LidarSemanticSegmentation/run (line 120)
predictedResult = semanticseg(I, algObj.PretrainedNetwork);
Error in lidar.labeler.AutomationAlgorithm/doRun (line 611)
videoLabels = run(this, frame);
Error in lidar.internal.lidarLabeler.tool.TemporalLabelingTool/runAlgorithm
Error in vision.internal.labeler.tool.AlgorithmTab/setAlgorithmModeAndExecute
Error in vision.internal.labeler.tool.AlgorithmTab
Error in internal.Callback.execute (line 128)
feval(callback, src, event);
Error in matlab.ui.internal.toolstrip.base.Action/PeerEventCallback (line 846)
internal.Callback.execute(this.PushPerformedFcn, this, eventdata);
Error in matlab.ui.internal.toolstrip.base.ActionInterface>@(event,data)PeerEventCallback(this,event,data) (line 57)
this.PeerEventListener = addlistener(this.Peer, ‘peerEvent’, @(event, data) PeerEventCallback(this, event, data));
Error in hgfeval (line 62)
feval(fcn{1},varargin{:},fcn{2:end});
Error in javaaddlistener>cbBridge (line 52)
hgfeval(response, java(o), e.JavaEvent)
Error in javaaddlistener>@(o,e)cbBridge(o,e,response) (line 47)
@(o,e) cbBridge(o,e,response));
classdef LidarSemanticSegmentation < lidar.labeler.AutomationAlgorithm
% LidarSemanticSegmentation Automation algorithm performs semantic
% segmentation in the point cloud.
% LidarSemanticSegmentation is an automation algorithm for segmenting
% a point cloud using SqueezeSegV2 semantic segmentation network
% which is trained on Pandaset data set.
%
% See also lidarLabeler, groundTruthLabeler
% lidar.labeler.AutomationAlgorithm.
% Copyright 2021 The MathWorks, Inc.
% ———————————————————————-
% Step 1: Define the required properties describing the algorithm. This
% includes Name, Description, and UserDirections.
properties(Constant)
% Name Algorithm Name
% Character vector specifying the name of the algorithm.
Name = ‘Lidar Semantic Segmentation’;
% Description Algorithm Description
% Character vector specifying the short description of the algorithm.
Description = ‘Segment the point cloud using SqueezeSegV2 network.’;
% UserDirections Algorithm Usage Directions
% Cell array of character vectors specifying directions for
% algorithm users to follow to use the algorithm.
UserDirections = {[‘ROI Label Definition Selection: select one of ‘ …
‘the ROI definitions to be labeled’], …
‘Run: Press RUN to run the automation algorithm. ‘, …
[‘Review and Modify: Review automated labels over the interval ‘, …
‘using playback controls. Modify/delete/add ROIs that were not ‘ …
‘satisfactorily automated at this stage. If the results are ‘ …
‘satisfactory, click Accept to accept the automated labels.’], …
[‘Accept/Cancel: If the results of automation are satisfactory, ‘ …
‘click Accept to accept all automated labels and return to ‘ …
‘manual labeling. If the results of automation are not ‘ …
‘satisfactory, click Cancel to return to manual labeling ‘ …
‘without saving the automated labels.’]};
end
% ———————————————————————
% Step 2: Define properties you want to use during the algorithm
% execution.
properties
% AllCategories
% AllCategories holds the default ‘unlabelled’, ‘Vegetation’,
% ‘Ground’, ‘Road’, ‘RoadMarkings’, ‘SideWalk’, ‘Car’, ‘Truck’,
% ‘OtherVehicle’, ‘Pedestrian’, ‘RoadBarriers’, ‘Signs’,
% ‘Buildings’ categorical types.
AllCategories = {‘unlabelled’};
% PretrainedNetwork
% PretrainedNetwork saves the pretrained SqueezeSegV2 network.
PretrainedNetwork
end
%———————————————————————-
% Note: this method needs to be included for lidarLabeler app to
% recognize it as using pointcloud
methods (Static)
% This method is static to allow the apps to call it and check the
% signal type before instantiation. When users refresh the
% algorithm list, we can quickly check and discard algorithms for
% any signal that is not support in a given app.
function isValid = checkSignalType(signalType)
isValid = (signalType == vision.labeler.loading.SignalType.PointCloud);
end
end
%———————————————————————-
% Step 3: Define methods used for setting up the algorithm.
methods
function isValid = checkLabelDefinition(algObj, labelDef)
% Only Voxel ROI label definitions are valid for the Lidar
% semantic segmentation algorithm.
isValid = labelDef.Type == lidarLabelType.Voxel;
if isValid
algObj.AllCategories{end+1} = labelDef.Name;
end
end
function isReady = checkSetup(algObj)
% Is there one selected ROI Label definition to automate.
isReady = ~isempty(algObj.SelectedLabelDefinitions);
end
end
%———————————————————————-
% Step 4: Specify algorithm execution. This controls what happens when
% the user presses RUN. Algorithm execution proceeds by first
% executing initialize on the first frame, followed by run on
% every frame, and terminate on the last frame.
methods
function initialize(algObj,~)
% Load the pretrained SqueezeSegV2 semantic segmentation network.
outputFolder = fullfile(tempdir, ‘Pandaset’);
pretrainedSqueezeSeg = load(fullfile(outputFolder,’trainedSqueezeSegV2PandasetNet.mat’));
% Store the network in the ‘PretrainedNetwork’ property of this object.
algObj.PretrainedNetwork = pretrainedSqueezeSeg.net;
end
function autoLabels = run(algObj, pointCloud)
% Setup categorical matrix with categories including
% ‘Vegetation’, ‘Ground’, ‘Road’, ‘RoadMarkings’, ‘SideWalk’,
% ‘Car’, ‘Truck’, ‘OtherVehicle’, ‘Pedestrian’, ‘RoadBarriers’,
% and ‘Signs’.
autoLabels = categorical(zeros(size(pointCloud.Location,1), size(pointCloud.Location,2)), …
0:12,algObj.AllCategories);
% Convert the input point cloud to five channel image.
I = helperPointCloudToImage(pointCloud);
% Predict the segmentation result.
predictedResult = semanticseg(I, algObj.PretrainedNetwork);
autoLabels(:) = predictedResult;
%using this area we would be able to continuously update the latest file on
% sending the output towards the CAN Network or atleast ensure that the
% item is obtainable
% This area would work the best.
%first we must
end
end
end
function image = helperPointCloudToImage(ptcloud)
% helperPointCloudToImage converts the point cloud to 5 channel image
image = ptcloud.Location;
image(:,5) = ptcloud.Intensity;
rangeData = iComputeRangeData(image(:,1),image(:,2),image(:,3));
image(:,4) = rangeData;
index = isnan(image);
image(index) = 0;
end
function rangeData = iComputeRangeData(xChannel,yChannel,zChannel)
rangeData = sqrt(xChannel.*xChannel+yChannel.*yChannel+zChannel.*zChannel);
endI have an error in my machine learning algorithm where it would display an issue with the image size. I am using a .pcd file different to pandaSet yet I am wondering about why theres an error with the network model. I cant seem to determine what creates the netSize and how would I influence it for a new set of pcd dataSet
Error is:
Error using
Input image size must be greater than [64 1856]. The minimum input image size must be equal to or
greater than the input size in image input layer of the network.
Error in ()
iCheckImage(I, netSize);
Error in (line 244)
params = iParseInputs(I, net, varargin{:});
Error in lidar.labeler.LidarSemanticSegmentation/run (line 120)
predictedResult = semanticseg(I, algObj.PretrainedNetwork);
Error in lidar.labeler.AutomationAlgorithm/doRun (line 611)
videoLabels = run(this, frame);
Error in lidar.internal.lidarLabeler.tool.TemporalLabelingTool/runAlgorithm
Error in vision.internal.labeler.tool.AlgorithmTab/setAlgorithmModeAndExecute
Error in vision.internal.labeler.tool.AlgorithmTab
Error in internal.Callback.execute (line 128)
feval(callback, src, event);
Error in matlab.ui.internal.toolstrip.base.Action/PeerEventCallback (line 846)
internal.Callback.execute(this.PushPerformedFcn, this, eventdata);
Error in matlab.ui.internal.toolstrip.base.ActionInterface>@(event,data)PeerEventCallback(this,event,data) (line 57)
this.PeerEventListener = addlistener(this.Peer, ‘peerEvent’, @(event, data) PeerEventCallback(this, event, data));
Error in hgfeval (line 62)
feval(fcn{1},varargin{:},fcn{2:end});
Error in javaaddlistener>cbBridge (line 52)
hgfeval(response, java(o), e.JavaEvent)
Error in javaaddlistener>@(o,e)cbBridge(o,e,response) (line 47)
@(o,e) cbBridge(o,e,response));
classdef LidarSemanticSegmentation < lidar.labeler.AutomationAlgorithm
% LidarSemanticSegmentation Automation algorithm performs semantic
% segmentation in the point cloud.
% LidarSemanticSegmentation is an automation algorithm for segmenting
% a point cloud using SqueezeSegV2 semantic segmentation network
% which is trained on Pandaset data set.
%
% See also lidarLabeler, groundTruthLabeler
% lidar.labeler.AutomationAlgorithm.
% Copyright 2021 The MathWorks, Inc.
% ———————————————————————-
% Step 1: Define the required properties describing the algorithm. This
% includes Name, Description, and UserDirections.
properties(Constant)
% Name Algorithm Name
% Character vector specifying the name of the algorithm.
Name = ‘Lidar Semantic Segmentation’;
% Description Algorithm Description
% Character vector specifying the short description of the algorithm.
Description = ‘Segment the point cloud using SqueezeSegV2 network.’;
% UserDirections Algorithm Usage Directions
% Cell array of character vectors specifying directions for
% algorithm users to follow to use the algorithm.
UserDirections = {[‘ROI Label Definition Selection: select one of ‘ …
‘the ROI definitions to be labeled’], …
‘Run: Press RUN to run the automation algorithm. ‘, …
[‘Review and Modify: Review automated labels over the interval ‘, …
‘using playback controls. Modify/delete/add ROIs that were not ‘ …
‘satisfactorily automated at this stage. If the results are ‘ …
‘satisfactory, click Accept to accept the automated labels.’], …
[‘Accept/Cancel: If the results of automation are satisfactory, ‘ …
‘click Accept to accept all automated labels and return to ‘ …
‘manual labeling. If the results of automation are not ‘ …
‘satisfactory, click Cancel to return to manual labeling ‘ …
‘without saving the automated labels.’]};
end
% ———————————————————————
% Step 2: Define properties you want to use during the algorithm
% execution.
properties
% AllCategories
% AllCategories holds the default ‘unlabelled’, ‘Vegetation’,
% ‘Ground’, ‘Road’, ‘RoadMarkings’, ‘SideWalk’, ‘Car’, ‘Truck’,
% ‘OtherVehicle’, ‘Pedestrian’, ‘RoadBarriers’, ‘Signs’,
% ‘Buildings’ categorical types.
AllCategories = {‘unlabelled’};
% PretrainedNetwork
% PretrainedNetwork saves the pretrained SqueezeSegV2 network.
PretrainedNetwork
end
%———————————————————————-
% Note: this method needs to be included for lidarLabeler app to
% recognize it as using pointcloud
methods (Static)
% This method is static to allow the apps to call it and check the
% signal type before instantiation. When users refresh the
% algorithm list, we can quickly check and discard algorithms for
% any signal that is not support in a given app.
function isValid = checkSignalType(signalType)
isValid = (signalType == vision.labeler.loading.SignalType.PointCloud);
end
end
%———————————————————————-
% Step 3: Define methods used for setting up the algorithm.
methods
function isValid = checkLabelDefinition(algObj, labelDef)
% Only Voxel ROI label definitions are valid for the Lidar
% semantic segmentation algorithm.
isValid = labelDef.Type == lidarLabelType.Voxel;
if isValid
algObj.AllCategories{end+1} = labelDef.Name;
end
end
function isReady = checkSetup(algObj)
% Is there one selected ROI Label definition to automate.
isReady = ~isempty(algObj.SelectedLabelDefinitions);
end
end
%———————————————————————-
% Step 4: Specify algorithm execution. This controls what happens when
% the user presses RUN. Algorithm execution proceeds by first
% executing initialize on the first frame, followed by run on
% every frame, and terminate on the last frame.
methods
function initialize(algObj,~)
% Load the pretrained SqueezeSegV2 semantic segmentation network.
outputFolder = fullfile(tempdir, ‘Pandaset’);
pretrainedSqueezeSeg = load(fullfile(outputFolder,’trainedSqueezeSegV2PandasetNet.mat’));
% Store the network in the ‘PretrainedNetwork’ property of this object.
algObj.PretrainedNetwork = pretrainedSqueezeSeg.net;
end
function autoLabels = run(algObj, pointCloud)
% Setup categorical matrix with categories including
% ‘Vegetation’, ‘Ground’, ‘Road’, ‘RoadMarkings’, ‘SideWalk’,
% ‘Car’, ‘Truck’, ‘OtherVehicle’, ‘Pedestrian’, ‘RoadBarriers’,
% and ‘Signs’.
autoLabels = categorical(zeros(size(pointCloud.Location,1), size(pointCloud.Location,2)), …
0:12,algObj.AllCategories);
% Convert the input point cloud to five channel image.
I = helperPointCloudToImage(pointCloud);
% Predict the segmentation result.
predictedResult = semanticseg(I, algObj.PretrainedNetwork);
autoLabels(:) = predictedResult;
%using this area we would be able to continuously update the latest file on
% sending the output towards the CAN Network or atleast ensure that the
% item is obtainable
% This area would work the best.
%first we must
end
end
end
function image = helperPointCloudToImage(ptcloud)
% helperPointCloudToImage converts the point cloud to 5 channel image
image = ptcloud.Location;
image(:,5) = ptcloud.Intensity;
rangeData = iComputeRangeData(image(:,1),image(:,2),image(:,3));
image(:,4) = rangeData;
index = isnan(image);
image(index) = 0;
end
function rangeData = iComputeRangeData(xChannel,yChannel,zChannel)
rangeData = sqrt(xChannel.*xChannel+yChannel.*yChannel+zChannel.*zChannel);
end I have an error in my machine learning algorithm where it would display an issue with the image size. I am using a .pcd file different to pandaSet yet I am wondering about why theres an error with the network model. I cant seem to determine what creates the netSize and how would I influence it for a new set of pcd dataSet
Error is:
Error using
Input image size must be greater than [64 1856]. The minimum input image size must be equal to or
greater than the input size in image input layer of the network.
Error in ()
iCheckImage(I, netSize);
Error in (line 244)
params = iParseInputs(I, net, varargin{:});
Error in lidar.labeler.LidarSemanticSegmentation/run (line 120)
predictedResult = semanticseg(I, algObj.PretrainedNetwork);
Error in lidar.labeler.AutomationAlgorithm/doRun (line 611)
videoLabels = run(this, frame);
Error in lidar.internal.lidarLabeler.tool.TemporalLabelingTool/runAlgorithm
Error in vision.internal.labeler.tool.AlgorithmTab/setAlgorithmModeAndExecute
Error in vision.internal.labeler.tool.AlgorithmTab
Error in internal.Callback.execute (line 128)
feval(callback, src, event);
Error in matlab.ui.internal.toolstrip.base.Action/PeerEventCallback (line 846)
internal.Callback.execute(this.PushPerformedFcn, this, eventdata);
Error in matlab.ui.internal.toolstrip.base.ActionInterface>@(event,data)PeerEventCallback(this,event,data) (line 57)
this.PeerEventListener = addlistener(this.Peer, ‘peerEvent’, @(event, data) PeerEventCallback(this, event, data));
Error in hgfeval (line 62)
feval(fcn{1},varargin{:},fcn{2:end});
Error in javaaddlistener>cbBridge (line 52)
hgfeval(response, java(o), e.JavaEvent)
Error in javaaddlistener>@(o,e)cbBridge(o,e,response) (line 47)
@(o,e) cbBridge(o,e,response));
classdef LidarSemanticSegmentation < lidar.labeler.AutomationAlgorithm
% LidarSemanticSegmentation Automation algorithm performs semantic
% segmentation in the point cloud.
% LidarSemanticSegmentation is an automation algorithm for segmenting
% a point cloud using SqueezeSegV2 semantic segmentation network
% which is trained on Pandaset data set.
%
% See also lidarLabeler, groundTruthLabeler
% lidar.labeler.AutomationAlgorithm.
% Copyright 2021 The MathWorks, Inc.
% ———————————————————————-
% Step 1: Define the required properties describing the algorithm. This
% includes Name, Description, and UserDirections.
properties(Constant)
% Name Algorithm Name
% Character vector specifying the name of the algorithm.
Name = ‘Lidar Semantic Segmentation’;
% Description Algorithm Description
% Character vector specifying the short description of the algorithm.
Description = ‘Segment the point cloud using SqueezeSegV2 network.’;
% UserDirections Algorithm Usage Directions
% Cell array of character vectors specifying directions for
% algorithm users to follow to use the algorithm.
UserDirections = {[‘ROI Label Definition Selection: select one of ‘ …
‘the ROI definitions to be labeled’], …
‘Run: Press RUN to run the automation algorithm. ‘, …
[‘Review and Modify: Review automated labels over the interval ‘, …
‘using playback controls. Modify/delete/add ROIs that were not ‘ …
‘satisfactorily automated at this stage. If the results are ‘ …
‘satisfactory, click Accept to accept the automated labels.’], …
[‘Accept/Cancel: If the results of automation are satisfactory, ‘ …
‘click Accept to accept all automated labels and return to ‘ …
‘manual labeling. If the results of automation are not ‘ …
‘satisfactory, click Cancel to return to manual labeling ‘ …
‘without saving the automated labels.’]};
end
% ———————————————————————
% Step 2: Define properties you want to use during the algorithm
% execution.
properties
% AllCategories
% AllCategories holds the default ‘unlabelled’, ‘Vegetation’,
% ‘Ground’, ‘Road’, ‘RoadMarkings’, ‘SideWalk’, ‘Car’, ‘Truck’,
% ‘OtherVehicle’, ‘Pedestrian’, ‘RoadBarriers’, ‘Signs’,
% ‘Buildings’ categorical types.
AllCategories = {‘unlabelled’};
% PretrainedNetwork
% PretrainedNetwork saves the pretrained SqueezeSegV2 network.
PretrainedNetwork
end
%———————————————————————-
% Note: this method needs to be included for lidarLabeler app to
% recognize it as using pointcloud
methods (Static)
% This method is static to allow the apps to call it and check the
% signal type before instantiation. When users refresh the
% algorithm list, we can quickly check and discard algorithms for
% any signal that is not support in a given app.
function isValid = checkSignalType(signalType)
isValid = (signalType == vision.labeler.loading.SignalType.PointCloud);
end
end
%———————————————————————-
% Step 3: Define methods used for setting up the algorithm.
methods
function isValid = checkLabelDefinition(algObj, labelDef)
% Only Voxel ROI label definitions are valid for the Lidar
% semantic segmentation algorithm.
isValid = labelDef.Type == lidarLabelType.Voxel;
if isValid
algObj.AllCategories{end+1} = labelDef.Name;
end
end
function isReady = checkSetup(algObj)
% Is there one selected ROI Label definition to automate.
isReady = ~isempty(algObj.SelectedLabelDefinitions);
end
end
%———————————————————————-
% Step 4: Specify algorithm execution. This controls what happens when
% the user presses RUN. Algorithm execution proceeds by first
% executing initialize on the first frame, followed by run on
% every frame, and terminate on the last frame.
methods
function initialize(algObj,~)
% Load the pretrained SqueezeSegV2 semantic segmentation network.
outputFolder = fullfile(tempdir, ‘Pandaset’);
pretrainedSqueezeSeg = load(fullfile(outputFolder,’trainedSqueezeSegV2PandasetNet.mat’));
% Store the network in the ‘PretrainedNetwork’ property of this object.
algObj.PretrainedNetwork = pretrainedSqueezeSeg.net;
end
function autoLabels = run(algObj, pointCloud)
% Setup categorical matrix with categories including
% ‘Vegetation’, ‘Ground’, ‘Road’, ‘RoadMarkings’, ‘SideWalk’,
% ‘Car’, ‘Truck’, ‘OtherVehicle’, ‘Pedestrian’, ‘RoadBarriers’,
% and ‘Signs’.
autoLabels = categorical(zeros(size(pointCloud.Location,1), size(pointCloud.Location,2)), …
0:12,algObj.AllCategories);
% Convert the input point cloud to five channel image.
I = helperPointCloudToImage(pointCloud);
% Predict the segmentation result.
predictedResult = semanticseg(I, algObj.PretrainedNetwork);
autoLabels(:) = predictedResult;
%using this area we would be able to continuously update the latest file on
% sending the output towards the CAN Network or atleast ensure that the
% item is obtainable
% This area would work the best.
%first we must
end
end
end
function image = helperPointCloudToImage(ptcloud)
% helperPointCloudToImage converts the point cloud to 5 channel image
image = ptcloud.Location;
image(:,5) = ptcloud.Intensity;
rangeData = iComputeRangeData(image(:,1),image(:,2),image(:,3));
image(:,4) = rangeData;
index = isnan(image);
image(index) = 0;
end
function rangeData = iComputeRangeData(xChannel,yChannel,zChannel)
rangeData = sqrt(xChannel.*xChannel+yChannel.*yChannel+zChannel.*zChannel);
end machine learning, neural network MATLAB Answers — New Questions
Placing a Matlab function block with a call to a Simulink function in a for each subsystem
I have a Matlab function block that calls a Simulink function. I am trying to place this block into a for each subsystem and i get the following error.
The MATLAB Function cannot be placed inside a subsystem containing a "For Each" block. This might be because of one or more of the following reasons: 1. The MATLAB Function has a data with scope "Data Store Memory". 2. The MATLAB Function calls Simulink functions.
Is there a workaround to this problem ?I have a Matlab function block that calls a Simulink function. I am trying to place this block into a for each subsystem and i get the following error.
The MATLAB Function cannot be placed inside a subsystem containing a "For Each" block. This might be because of one or more of the following reasons: 1. The MATLAB Function has a data with scope "Data Store Memory". 2. The MATLAB Function calls Simulink functions.
Is there a workaround to this problem ? I have a Matlab function block that calls a Simulink function. I am trying to place this block into a for each subsystem and i get the following error.
The MATLAB Function cannot be placed inside a subsystem containing a "For Each" block. This might be because of one or more of the following reasons: 1. The MATLAB Function has a data with scope "Data Store Memory". 2. The MATLAB Function calls Simulink functions.
Is there a workaround to this problem ? for each subsystem, simulink function MATLAB Answers — New Questions