Hi all,
Say I am working on a project-enabled git repo which gives me the Project tab whenever I open my *.prj file. Everything works fine and all, until when it’s time for me to commit my changes. Let’s say I wanna commit all changes, so logically I would use the ‘Commit’ button in the Project tab:

Eventhough it is just small changes, it takes almost a minute to for the committing to complete! This is shown by this rotating circle progress indicator ‘Checking in files’:

In contrast, if I were to commit the files individually using the right-click context menu like this:

It takes less than a second! Why is this, and if this is a bug, please fix it since committing using the button is convenient to commit all changes at once.

Thank you!Hi all,
Say I am working on a project-enabled git repo which gives me the Project tab whenever I open my *.prj file. Everything works fine and all, until when it’s time for me to commit my changes. Let’s say I wanna commit all changes, so logically I would use the ‘Commit’ button in the Project tab:

Eventhough it is just small changes, it takes almost a minute to for the committing to complete! This is shown by this rotating circle progress indicator ‘Checking in files’:

In contrast, if I were to commit the files individually using the right-click context menu like this:

It takes less than a second! Why is this, and if this is a bug, please fix it since committing using the button is convenient to commit all changes at once.

Thank you! Hi all,
Say I am working on a project-enabled git repo which gives me the Project tab whenever I open my *.prj file. Everything works fine and all, until when it’s time for me to commit my changes. Let’s say I wanna commit all changes, so logically I would use the ‘Commit’ button in the Project tab:

Eventhough it is just small changes, it takes almost a minute to for the committing to complete! This is shown by this rotating circle progress indicator ‘Checking in files’:

In contrast, if I were to commit the files individually using the right-click context menu like this:

It takes less than a second! Why is this, and if this is a bug, please fix it since committing using the button is convenient to commit all changes at once.

Thank you! matlab, project, git, commit MATLAB Answers — New Questions

​

I am new in matlab and I am trying to use ‘divideind’ to divide my data in order, but unfortunately it gives me this:
trainInd: [1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 … ] (1×1418 double)
valInd: [1×0 double]
testInd: [1×0 double]
I would appreciate it if you tell me where is the problem?
this is my code:
X = data.inputs;

% Define the dependent variable
y = data.output;
Q = length(y);

% Define the split points
train_end = 1418;
val_end = 1773;
test_end = Q;

% Assign the indices
train_indices = 1:train_end;
val_indices = (train_end + 1):val_end;
test_indices = (val_end + 1):test_end;

% Use divideind to ensure proper division
[train_indices,val_indices,test_indices] = divideind(Q,train_indices,val_indices,test_indices);

% Divide the data into training and testing sets
x_train = log(X(train_indices, :));
x_valid = log(X(val_indices, :));
x_test = log(X(test_indices, :));
y_train = log(y(train_indices));
y_valid = log(y(val_indices));
y_test = log(y(test_indices));

% Transpose the data to fit the input format of the neural network
inputs_train = x_train’;
outputs_train = y_train’;
inputs_validation = x_valid’ ;
outputs_valid = y_valid’;
inputs_test = x_test’;
outputs_test = y_test’;

% Initialize arrays to store RMSE values
train_rmse = zeros(1, 10);
Valid_rmse = zeros(1, 10);
test_rmse = zeros(1, 10);

for i = 1:10
hiddenLayerSize = [i, i];
net = fitnet(hiddenLayerSize, ‘trainlm’);
net.trainParam.epochs = 200;
net.layers{1}.transferFcn = ‘poslin’;
net.layers{2}.transferFcn = ‘logsig’;

net.divideFcn = ‘divideind’;
net.divideMode = ‘sample’;
net.divideParam.trainInd = train_indices;
net.divideParam.valInd = val_indices;
net.divideParam.testInd = test_indices;

[net,tr] = train(net, inputs_train, outputs_train);

% Predict on training data
train_predictions = exp(net(inputs_train(:,tr.trainInd)));
yTrainTrue = exp(outputs_train(:,tr.trainInd));
train_rmse(i) = sqrt(mean((train_predictions – yTrainTrue).^2));
% Predict on Validation data
Valid_predictions = exp(net(inputs_validation(:,tr.valInd)));
yValTrue = exp(outputs_valid(:,tr.valInd));
Valid_rmse(i) = sqrt(mean((Valid_predictions – yValTrue).^2));
% Predict on Validation data
test_predictions = exp(net(inputs_test(:,tr.testInd)));
yTestTrue = exp(outputs_test(:,tr.testInd));
test_rmse(i) = sqrt(mean((test_predictions – yTestTrue).^2));

endI am new in matlab and I am trying to use ‘divideind’ to divide my data in order, but unfortunately it gives me this:
trainInd: [1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 … ] (1×1418 double)
valInd: [1×0 double]
testInd: [1×0 double]
I would appreciate it if you tell me where is the problem?
this is my code:
X = data.inputs;

% Define the dependent variable
y = data.output;
Q = length(y);

% Define the split points
train_end = 1418;
val_end = 1773;
test_end = Q;

% Assign the indices
train_indices = 1:train_end;
val_indices = (train_end + 1):val_end;
test_indices = (val_end + 1):test_end;

% Use divideind to ensure proper division
[train_indices,val_indices,test_indices] = divideind(Q,train_indices,val_indices,test_indices);

% Divide the data into training and testing sets
x_train = log(X(train_indices, :));
x_valid = log(X(val_indices, :));
x_test = log(X(test_indices, :));
y_train = log(y(train_indices));
y_valid = log(y(val_indices));
y_test = log(y(test_indices));

% Transpose the data to fit the input format of the neural network
inputs_train = x_train’;
outputs_train = y_train’;
inputs_validation = x_valid’ ;
outputs_valid = y_valid’;
inputs_test = x_test’;
outputs_test = y_test’;

% Initialize arrays to store RMSE values
train_rmse = zeros(1, 10);
Valid_rmse = zeros(1, 10);
test_rmse = zeros(1, 10);

for i = 1:10
hiddenLayerSize = [i, i];
net = fitnet(hiddenLayerSize, ‘trainlm’);
net.trainParam.epochs = 200;
net.layers{1}.transferFcn = ‘poslin’;
net.layers{2}.transferFcn = ‘logsig’;

net.divideFcn = ‘divideind’;
net.divideMode = ‘sample’;
net.divideParam.trainInd = train_indices;
net.divideParam.valInd = val_indices;
net.divideParam.testInd = test_indices;

[net,tr] = train(net, inputs_train, outputs_train);

% Predict on training data
train_predictions = exp(net(inputs_train(:,tr.trainInd)));
yTrainTrue = exp(outputs_train(:,tr.trainInd));
train_rmse(i) = sqrt(mean((train_predictions – yTrainTrue).^2));
% Predict on Validation data
Valid_predictions = exp(net(inputs_validation(:,tr.valInd)));
yValTrue = exp(outputs_valid(:,tr.valInd));
Valid_rmse(i) = sqrt(mean((Valid_predictions – yValTrue).^2));
% Predict on Validation data
test_predictions = exp(net(inputs_test(:,tr.testInd)));
yTestTrue = exp(outputs_test(:,tr.testInd));
test_rmse(i) = sqrt(mean((test_predictions – yTestTrue).^2));

end I am new in matlab and I am trying to use ‘divideind’ to divide my data in order, but unfortunately it gives me this:
trainInd: [1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 … ] (1×1418 double)
valInd: [1×0 double]
testInd: [1×0 double]
I would appreciate it if you tell me where is the problem?
this is my code:
X = data.inputs;

% Define the dependent variable
y = data.output;
Q = length(y);

% Define the split points
train_end = 1418;
val_end = 1773;
test_end = Q;

% Assign the indices
train_indices = 1:train_end;
val_indices = (train_end + 1):val_end;
test_indices = (val_end + 1):test_end;

% Use divideind to ensure proper division
[train_indices,val_indices,test_indices] = divideind(Q,train_indices,val_indices,test_indices);

% Divide the data into training and testing sets
x_train = log(X(train_indices, :));
x_valid = log(X(val_indices, :));
x_test = log(X(test_indices, :));
y_train = log(y(train_indices));
y_valid = log(y(val_indices));
y_test = log(y(test_indices));

% Transpose the data to fit the input format of the neural network
inputs_train = x_train’;
outputs_train = y_train’;
inputs_validation = x_valid’ ;
outputs_valid = y_valid’;
inputs_test = x_test’;
outputs_test = y_test’;

% Initialize arrays to store RMSE values
train_rmse = zeros(1, 10);
Valid_rmse = zeros(1, 10);
test_rmse = zeros(1, 10);

for i = 1:10
hiddenLayerSize = [i, i];
net = fitnet(hiddenLayerSize, ‘trainlm’);
net.trainParam.epochs = 200;
net.layers{1}.transferFcn = ‘poslin’;
net.layers{2}.transferFcn = ‘logsig’;

net.divideFcn = ‘divideind’;
net.divideMode = ‘sample’;
net.divideParam.trainInd = train_indices;
net.divideParam.valInd = val_indices;
net.divideParam.testInd = test_indices;

[net,tr] = train(net, inputs_train, outputs_train);

% Predict on training data
train_predictions = exp(net(inputs_train(:,tr.trainInd)));
yTrainTrue = exp(outputs_train(:,tr.trainInd));
train_rmse(i) = sqrt(mean((train_predictions – yTrainTrue).^2));
% Predict on Validation data
Valid_predictions = exp(net(inputs_validation(:,tr.valInd)));
yValTrue = exp(outputs_valid(:,tr.valInd));
Valid_rmse(i) = sqrt(mean((Valid_predictions – yValTrue).^2));
% Predict on Validation data
test_predictions = exp(net(inputs_test(:,tr.testInd)));
yTestTrue = exp(outputs_test(:,tr.testInd));
test_rmse(i) = sqrt(mean((test_predictions – yTestTrue).^2));

end divideind, ann, split data MATLAB Answers — New Questions

​

Hi guys,
Can you please tell me how can I get MTF from the PSF. PSF is the matrix of 400X400 taken from the camera. Please see attached mat file.
Thank you very much.Hi guys,
Can you please tell me how can I get MTF from the PSF. PSF is the matrix of 400X400 taken from the camera. Please see attached mat file.
Thank you very much. Hi guys,
Can you please tell me how can I get MTF from the PSF. PSF is the matrix of 400X400 taken from the camera. Please see attached mat file.
Thank you very much. psf, mtf MATLAB Answers — New Questions

​

Below is a small script for using the polyfit command but surprisingly the last command gives me a completely wrong polynomial p. I don’t understand why. Thanks in advance for your help.
Below the script is the response from my version of MATLAB (R2015a).
%————————————————————————————————————–
%butta_sto_test
%
clear all
clc
x=[1:9]
y=[5,6,10,20,28,33,34,36,42]
p=polyfit(x,y,1)
[p,S]=polyfit(x,y,1)
[p,S,mu]=polyfit(x,y,1)
%———————————————————————————————————————-

x =

1 2 3 4 5 6 7 8 9

y =

5 6 10 20 28 33 34 36 42

p =

4.9833 -1.1389

p =

4.9833 -1.1389

S =

R: [2×2 double]
df: 7
normr: 8.4581

p =

13.6474 23.7778

S =

R: [2×2 double]
df: 7
normr: 8.4581

mu =

5.0000
2.7386Below is a small script for using the polyfit command but surprisingly the last command gives me a completely wrong polynomial p. I don’t understand why. Thanks in advance for your help.
Below the script is the response from my version of MATLAB (R2015a).
%————————————————————————————————————–
%butta_sto_test
%
clear all
clc
x=[1:9]
y=[5,6,10,20,28,33,34,36,42]
p=polyfit(x,y,1)
[p,S]=polyfit(x,y,1)
[p,S,mu]=polyfit(x,y,1)
%———————————————————————————————————————-

x =

1 2 3 4 5 6 7 8 9

y =

5 6 10 20 28 33 34 36 42

p =

4.9833 -1.1389

p =

4.9833 -1.1389

S =

R: [2×2 double]
df: 7
normr: 8.4581

p =

13.6474 23.7778

S =

R: [2×2 double]
df: 7
normr: 8.4581

mu =

5.0000
2.7386 Below is a small script for using the polyfit command but surprisingly the last command gives me a completely wrong polynomial p. I don’t understand why. Thanks in advance for your help.
Below the script is the response from my version of MATLAB (R2015a).
%————————————————————————————————————–
%butta_sto_test
%
clear all
clc
x=[1:9]
y=[5,6,10,20,28,33,34,36,42]
p=polyfit(x,y,1)
[p,S]=polyfit(x,y,1)
[p,S,mu]=polyfit(x,y,1)
%———————————————————————————————————————-

x =

1 2 3 4 5 6 7 8 9

y =

5 6 10 20 28 33 34 36 42

p =

4.9833 -1.1389

p =

4.9833 -1.1389

S =

R: [2×2 double]
df: 7
normr: 8.4581

p =

13.6474 23.7778

S =

R: [2×2 double]
df: 7
normr: 8.4581

mu =

5.0000
2.7386 polyfit MATLAB Answers — New Questions

​

I’m trying to get the real-time orientation of the IMU9250 sensor by following the documentation: "Estimating Orientation Using Inertial Sensor Fusion and MPU-9250"
Can I customize the HelperOrientationViewer() function? I want to add another 3D object to the 3D plot. I also want to change the normal 3D object to another mesh STL object. and I want to change the scale of each axis to be more bigger. How can I do these?
I tryed to use poseplot() function, but it is too slow comparing to HelperOrientationViewer() functionI’m trying to get the real-time orientation of the IMU9250 sensor by following the documentation: "Estimating Orientation Using Inertial Sensor Fusion and MPU-9250"
Can I customize the HelperOrientationViewer() function? I want to add another 3D object to the 3D plot. I also want to change the normal 3D object to another mesh STL object. and I want to change the scale of each axis to be more bigger. How can I do these?
I tryed to use poseplot() function, but it is too slow comparing to HelperOrientationViewer() function I’m trying to get the real-time orientation of the IMU9250 sensor by following the documentation: "Estimating Orientation Using Inertial Sensor Fusion and MPU-9250"
Can I customize the HelperOrientationViewer() function? I want to add another 3D object to the 3D plot. I also want to change the normal 3D object to another mesh STL object. and I want to change the scale of each axis to be more bigger. How can I do these?
I tryed to use poseplot() function, but it is too slow comparing to HelperOrientationViewer() function arduino, sensor fusion, helperorientationviewer, imu9250, graphics, poseplot MATLAB Answers — New Questions

​

Please help!
3 is correct for Test 1, but I am going crazy trying to figure out why 5 is incorrect for Test 2.
function numfreeze = freezing(a)
numfreeze = sum(a>=32);
endPlease help!
3 is correct for Test 1, but I am going crazy trying to figure out why 5 is incorrect for Test 2.
function numfreeze = freezing(a)
numfreeze = sum(a>=32);
end Please help!
3 is correct for Test 1, but I am going crazy trying to figure out why 5 is incorrect for Test 2.
function numfreeze = freezing(a)
numfreeze = sum(a>=32);
end logical array MATLAB Answers — New Questions

​

Hi. I am using batch() to run a function with a par-for loop inside. When I run it as a script (instead of a function), everything works fine. However, when I replace the script with the equivalent function, I get an error. Here are the details:
%(A) Using batch() to call script. This works fine!
job = batch(parcluster(‘local’), ‘batchscript’,’Pool’,5);

%(B) Using batch() to call function. This produces an error.
jm=6;
job = batch(parcluster(‘local’),’batchfun’,0,{jm},’Pool’,5);
The script (batchscript.m) I am running in A, looks something like that:
jm = 6;
run(‘Paths.m’) %This creates ‘pth’ using ‘jm’

parfor vh = 1:length(alld)
parfun01(vh,jm,pth)
end
The function (batchfun.m) I am running in B, looks something like that:
function batchfun(jm)

run(‘Paths.m’) %This creates ‘pth’ using ‘jm’

parfor vh = 1:length(alld)
parfun01(vh,jm,pth)
end
They reason why I decided to turn this from a scrip to a function was because I wanted to pass jm as an input, instead of always changing the script. However, I cannot understand why it works perfectly fine as a script, but not as a function.
The error I am getting when running B) is the following:
getReport(job.Tasks(1).Error)
ans =
‘Error using batchfun (line 66)
The source code (E:Analysisbatchfun.m) for the parfor-loop that is trying to
execute on the worker could not be found.
Caused by:
Unrecognized function or variable ‘pth’.
Error using remoteParallelFunction (line 84)
Worker unable to find file.
Unrecognized function or variable ‘pth’.’
Anyone could please help me with what’s wrong? Thanks!Hi. I am using batch() to run a function with a par-for loop inside. When I run it as a script (instead of a function), everything works fine. However, when I replace the script with the equivalent function, I get an error. Here are the details:
%(A) Using batch() to call script. This works fine!
job = batch(parcluster(‘local’), ‘batchscript’,’Pool’,5);

%(B) Using batch() to call function. This produces an error.
jm=6;
job = batch(parcluster(‘local’),’batchfun’,0,{jm},’Pool’,5);
The script (batchscript.m) I am running in A, looks something like that:
jm = 6;
run(‘Paths.m’) %This creates ‘pth’ using ‘jm’

parfor vh = 1:length(alld)
parfun01(vh,jm,pth)
end
The function (batchfun.m) I am running in B, looks something like that:
function batchfun(jm)

run(‘Paths.m’) %This creates ‘pth’ using ‘jm’

parfor vh = 1:length(alld)
parfun01(vh,jm,pth)
end
They reason why I decided to turn this from a scrip to a function was because I wanted to pass jm as an input, instead of always changing the script. However, I cannot understand why it works perfectly fine as a script, but not as a function.
The error I am getting when running B) is the following:
getReport(job.Tasks(1).Error)
ans =
‘Error using batchfun (line 66)
The source code (E:Analysisbatchfun.m) for the parfor-loop that is trying to
execute on the worker could not be found.
Caused by:
Unrecognized function or variable ‘pth’.
Error using remoteParallelFunction (line 84)
Worker unable to find file.
Unrecognized function or variable ‘pth’.’
Anyone could please help me with what’s wrong? Thanks! Hi. I am using batch() to run a function with a par-for loop inside. When I run it as a script (instead of a function), everything works fine. However, when I replace the script with the equivalent function, I get an error. Here are the details:
%(A) Using batch() to call script. This works fine!
job = batch(parcluster(‘local’), ‘batchscript’,’Pool’,5);

%(B) Using batch() to call function. This produces an error.
jm=6;
job = batch(parcluster(‘local’),’batchfun’,0,{jm},’Pool’,5);
The script (batchscript.m) I am running in A, looks something like that:
jm = 6;
run(‘Paths.m’) %This creates ‘pth’ using ‘jm’

parfor vh = 1:length(alld)
parfun01(vh,jm,pth)
end
The function (batchfun.m) I am running in B, looks something like that:
function batchfun(jm)

run(‘Paths.m’) %This creates ‘pth’ using ‘jm’

parfor vh = 1:length(alld)
parfun01(vh,jm,pth)
end
They reason why I decided to turn this from a scrip to a function was because I wanted to pass jm as an input, instead of always changing the script. However, I cannot understand why it works perfectly fine as a script, but not as a function.
The error I am getting when running B) is the following:
getReport(job.Tasks(1).Error)
ans =
‘Error using batchfun (line 66)
The source code (E:Analysisbatchfun.m) for the parfor-loop that is trying to
execute on the worker could not be found.
Caused by:
Unrecognized function or variable ‘pth’.
Error using remoteParallelFunction (line 84)
Worker unable to find file.
Unrecognized function or variable ‘pth’.’
Anyone could please help me with what’s wrong? Thanks! batch, parfor, parallel computing, parallel MATLAB Answers — New Questions

​