Hi all, I am working on this curve fitting project and I am trying out different methods to optimise the run time. One of the methods I am trying involes having 2 seperate scripts, with one script containing the function used for fitting and curve fitting (call this script 1), and the other script containing codes to load the data and process the data (call this script 2). However, when I try to call script 1 from 2, I get a ton of error messages. Could I please ask why is this the problem? Thank you! My codes are attached below:

tic
%% Preparation
clc; clear
format short
TAdata = readmatrix("FCPIB-293K-2.5mW-400nm-Jan072021 -ibg -bg -chirp.csv"); % insert file path within parenthesis
MBdata = readmatrix("carrier temp.xlsx");
P = load("Steady_State_Parameter_Values.mat");
Function = ‘Transient_Absorption’;

%% Preamble

% Fundamental constants
h = 4.1356677*10^-15; % units: eV/ Hz
c = 3*10^8; % SI units
kB = 8.617333268*10^-5; % units: eV/ K

% Data
Wavelength = TAdata(:, 1);% units: nm
E = (h*c)./(Wavelength*10^-9);
delay_t = TAdata(1, :);
delay_T = MBdata(:, 2);
carrier_T = MBdata(:, 3);

% Data for fitting
min_E = 1.5;
max_E = 2.0;
Range_E = E >= min_E & E <= max_E;
Range_W = Wavelength >= (h*c)/(max_E*10^-9) & Wavelength <= (h*c)/(min_E*10^-9);
E_p = E(Range_E); % selected probe energies
for n = 1:length(carrier_T)
a(1, n) = find(delay_T(n) == delay_t);
data_new2 = TAdata(Range_W, a);
end

%% Data for fitting and calling fitting function & solver
for i = 1:length(delay_T)
p = P.p;
A1 = p(1,1);
A2 = p(1,2);
Eg = p(1,3);
Eb = p(1,4);
R = p(1,5);
g = p(1,6);
deltaAbs = data_new2(:, i);
lb = [0, 0, 0, 0.3, 0, 0]; ub = [20, 0.05, 0.05, 2, 2, 1];
x0 = [1.6244, 0.0346, 0.03, 1.5139, 1, 0.3];
carrierT = carrier_T(i);
[x] = TA_fitting_function(A1, A2, Eg, Eb, R, g, x0,x,carrierT,E_p,deltaAbs,lb,ub,i,LegendText, Function);
end

%% Table of parameter values
time_delay = [‘0.5 ps’; ‘1.0 ps’; ‘2.0 ps’; ‘4.0 ps’];
Eg_prime = x(:, 1);
Eb_prime = x(:, 2);
g_prime = x(:, 3);
Ef_q = x(:, 4);
f1 = x(:, 5);
f2 = x(:, 6);
T = table(time_delay, Eg_prime, Eb_prime, g_prime, Ef_q, f1, f2);
disp(T)

tocHi all, I am working on this curve fitting project and I am trying out different methods to optimise the run time. One of the methods I am trying involes having 2 seperate scripts, with one script containing the function used for fitting and curve fitting (call this script 1), and the other script containing codes to load the data and process the data (call this script 2). However, when I try to call script 1 from 2, I get a ton of error messages. Could I please ask why is this the problem? Thank you! My codes are attached below:

tic
%% Preparation
clc; clear
format short
TAdata = readmatrix("FCPIB-293K-2.5mW-400nm-Jan072021 -ibg -bg -chirp.csv"); % insert file path within parenthesis
MBdata = readmatrix("carrier temp.xlsx");
P = load("Steady_State_Parameter_Values.mat");
Function = ‘Transient_Absorption’;

%% Preamble

% Fundamental constants
h = 4.1356677*10^-15; % units: eV/ Hz
c = 3*10^8; % SI units
kB = 8.617333268*10^-5; % units: eV/ K

% Data
Wavelength = TAdata(:, 1);% units: nm
E = (h*c)./(Wavelength*10^-9);
delay_t = TAdata(1, :);
delay_T = MBdata(:, 2);
carrier_T = MBdata(:, 3);

% Data for fitting
min_E = 1.5;
max_E = 2.0;
Range_E = E >= min_E & E <= max_E;
Range_W = Wavelength >= (h*c)/(max_E*10^-9) & Wavelength <= (h*c)/(min_E*10^-9);
E_p = E(Range_E); % selected probe energies
for n = 1:length(carrier_T)
a(1, n) = find(delay_T(n) == delay_t);
data_new2 = TAdata(Range_W, a);
end

%% Data for fitting and calling fitting function & solver
for i = 1:length(delay_T)
p = P.p;
A1 = p(1,1);
A2 = p(1,2);
Eg = p(1,3);
Eb = p(1,4);
R = p(1,5);
g = p(1,6);
deltaAbs = data_new2(:, i);
lb = [0, 0, 0, 0.3, 0, 0]; ub = [20, 0.05, 0.05, 2, 2, 1];
x0 = [1.6244, 0.0346, 0.03, 1.5139, 1, 0.3];
carrierT = carrier_T(i);
[x] = TA_fitting_function(A1, A2, Eg, Eb, R, g, x0,x,carrierT,E_p,deltaAbs,lb,ub,i,LegendText, Function);
end

%% Table of parameter values
time_delay = [‘0.5 ps’; ‘1.0 ps’; ‘2.0 ps’; ‘4.0 ps’];
Eg_prime = x(:, 1);
Eb_prime = x(:, 2);
g_prime = x(:, 3);
Ef_q = x(:, 4);
f1 = x(:, 5);
f2 = x(:, 6);
T = table(time_delay, Eg_prime, Eb_prime, g_prime, Ef_q, f1, f2);
disp(T)

toc Hi all, I am working on this curve fitting project and I am trying out different methods to optimise the run time. One of the methods I am trying involes having 2 seperate scripts, with one script containing the function used for fitting and curve fitting (call this script 1), and the other script containing codes to load the data and process the data (call this script 2). However, when I try to call script 1 from 2, I get a ton of error messages. Could I please ask why is this the problem? Thank you! My codes are attached below:

tic
%% Preparation
clc; clear
format short
TAdata = readmatrix("FCPIB-293K-2.5mW-400nm-Jan072021 -ibg -bg -chirp.csv"); % insert file path within parenthesis
MBdata = readmatrix("carrier temp.xlsx");
P = load("Steady_State_Parameter_Values.mat");
Function = ‘Transient_Absorption’;

%% Preamble

% Fundamental constants
h = 4.1356677*10^-15; % units: eV/ Hz
c = 3*10^8; % SI units
kB = 8.617333268*10^-5; % units: eV/ K

% Data
Wavelength = TAdata(:, 1);% units: nm
E = (h*c)./(Wavelength*10^-9);
delay_t = TAdata(1, :);
delay_T = MBdata(:, 2);
carrier_T = MBdata(:, 3);

% Data for fitting
min_E = 1.5;
max_E = 2.0;
Range_E = E >= min_E & E <= max_E;
Range_W = Wavelength >= (h*c)/(max_E*10^-9) & Wavelength <= (h*c)/(min_E*10^-9);
E_p = E(Range_E); % selected probe energies
for n = 1:length(carrier_T)
a(1, n) = find(delay_T(n) == delay_t);
data_new2 = TAdata(Range_W, a);
end

%% Data for fitting and calling fitting function & solver
for i = 1:length(delay_T)
p = P.p;
A1 = p(1,1);
A2 = p(1,2);
Eg = p(1,3);
Eb = p(1,4);
R = p(1,5);
g = p(1,6);
deltaAbs = data_new2(:, i);
lb = [0, 0, 0, 0.3, 0, 0]; ub = [20, 0.05, 0.05, 2, 2, 1];
x0 = [1.6244, 0.0346, 0.03, 1.5139, 1, 0.3];
carrierT = carrier_T(i);
[x] = TA_fitting_function(A1, A2, Eg, Eb, R, g, x0,x,carrierT,E_p,deltaAbs,lb,ub,i,LegendText, Function);
end

%% Table of parameter values
time_delay = [‘0.5 ps’; ‘1.0 ps’; ‘2.0 ps’; ‘4.0 ps’];
Eg_prime = x(:, 1);
Eb_prime = x(:, 2);
g_prime = x(:, 3);
Ef_q = x(:, 4);
f1 = x(:, 5);
f2 = x(:, 6);
T = table(time_delay, Eg_prime, Eb_prime, g_prime, Ef_q, f1, f2);
disp(T)

toc curve fitting MATLAB Answers — New Questions

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So I would like to conduct PCA on a dataset I have that is of sample size 23 and feature size 813 (nxp = 23×813). However, when I run the pca function, the coeff variable returned is blank. why is this the case? I am aware my sample size: feature size ratio is very low, but the function returned a 813×22 coefficient matrix when I ran it on my data before I processed it (transformed nonnormally distributed data & feature scaling) so I know it is not because of unsuitable data size.
I have attached a copy of the data I am trying to use if anyone is able to help; thanks!
[coeff, ~, latent] = pca(deltaEBC);
UPDATE: I was feature scaling by taking feature X, subtracting the mean of X, and dividing by the standard deviation of X. I changed this to simply subtracting the mean and not dividing by the std, and now the pca function does return a 813 x 22 coeff I was looking for. I just don’t know why?So I would like to conduct PCA on a dataset I have that is of sample size 23 and feature size 813 (nxp = 23×813). However, when I run the pca function, the coeff variable returned is blank. why is this the case? I am aware my sample size: feature size ratio is very low, but the function returned a 813×22 coefficient matrix when I ran it on my data before I processed it (transformed nonnormally distributed data & feature scaling) so I know it is not because of unsuitable data size.
I have attached a copy of the data I am trying to use if anyone is able to help; thanks!
[coeff, ~, latent] = pca(deltaEBC);
UPDATE: I was feature scaling by taking feature X, subtracting the mean of X, and dividing by the standard deviation of X. I changed this to simply subtracting the mean and not dividing by the std, and now the pca function does return a 813 x 22 coeff I was looking for. I just don’t know why? So I would like to conduct PCA on a dataset I have that is of sample size 23 and feature size 813 (nxp = 23×813). However, when I run the pca function, the coeff variable returned is blank. why is this the case? I am aware my sample size: feature size ratio is very low, but the function returned a 813×22 coefficient matrix when I ran it on my data before I processed it (transformed nonnormally distributed data & feature scaling) so I know it is not because of unsuitable data size.
I have attached a copy of the data I am trying to use if anyone is able to help; thanks!
[coeff, ~, latent] = pca(deltaEBC);
UPDATE: I was feature scaling by taking feature X, subtracting the mean of X, and dividing by the standard deviation of X. I changed this to simply subtracting the mean and not dividing by the std, and now the pca function does return a 813 x 22 coeff I was looking for. I just don’t know why? pca MATLAB Answers — New Questions

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I have some scripts that directly create Signal Builder. How to solve the problem of signal builder being invalid after running the script in Matlab 2023b?I have some scripts that directly create Signal Builder. How to solve the problem of signal builder being invalid after running the script in Matlab 2023b? I have some scripts that directly create Signal Builder. How to solve the problem of signal builder being invalid after running the script in Matlab 2023b? signal builder MATLAB Answers — New Questions

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I am using Matlab 2023a to insert an FMU block into my Simulink model with the following two lines of code:
>> addpath(‘path/of/the/fmu/file’)
>> fmu_block = add_block(‘simulink_extras/FMU Import/FMU’, ‘MyModel/MyFMU’, ‘FMUName’, ‘fmu_file.fmu’);
The FMU block is successfully inserted into my model, and everything is currently working well. When I double-click on the FMU block, I can see options to enable or disable the visibility of each output port and internal variable:

Now, I’m wondering how I can use a Matlab script to control the visibility of output ports or variables. I’ve already attempted to retrieve port information using get_param(…), such as this:
port_name = get_param(‘Model/FMU/1’, ‘Name’);
But unfortunately, Matlab gives me this error:
Invalid Simulink object name: ‘Model/FMU/1’.
Caused by:
‘FMU’ is not a SubSystem block.
Therefore, the question remains: How can I retrieve or modify the visibility parameter of the ports and variables within an FMU block? I would appreciate any assistance anyone can provide.I am using Matlab 2023a to insert an FMU block into my Simulink model with the following two lines of code:
>> addpath(‘path/of/the/fmu/file’)
>> fmu_block = add_block(‘simulink_extras/FMU Import/FMU’, ‘MyModel/MyFMU’, ‘FMUName’, ‘fmu_file.fmu’);
The FMU block is successfully inserted into my model, and everything is currently working well. When I double-click on the FMU block, I can see options to enable or disable the visibility of each output port and internal variable:

Now, I’m wondering how I can use a Matlab script to control the visibility of output ports or variables. I’ve already attempted to retrieve port information using get_param(…), such as this:
port_name = get_param(‘Model/FMU/1’, ‘Name’);
But unfortunately, Matlab gives me this error:
Invalid Simulink object name: ‘Model/FMU/1’.
Caused by:
‘FMU’ is not a SubSystem block.
Therefore, the question remains: How can I retrieve or modify the visibility parameter of the ports and variables within an FMU block? I would appreciate any assistance anyone can provide. I am using Matlab 2023a to insert an FMU block into my Simulink model with the following two lines of code:
>> addpath(‘path/of/the/fmu/file’)
>> fmu_block = add_block(‘simulink_extras/FMU Import/FMU’, ‘MyModel/MyFMU’, ‘FMUName’, ‘fmu_file.fmu’);
The FMU block is successfully inserted into my model, and everything is currently working well. When I double-click on the FMU block, I can see options to enable or disable the visibility of each output port and internal variable:

Now, I’m wondering how I can use a Matlab script to control the visibility of output ports or variables. I’ve already attempted to retrieve port information using get_param(…), such as this:
port_name = get_param(‘Model/FMU/1’, ‘Name’);
But unfortunately, Matlab gives me this error:
Invalid Simulink object name: ‘Model/FMU/1’.
Caused by:
‘FMU’ is not a SubSystem block.
Therefore, the question remains: How can I retrieve or modify the visibility parameter of the ports and variables within an FMU block? I would appreciate any assistance anyone can provide. fmu, visibility, set_param MATLAB Answers — New Questions

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Is there any way to enter debug mode, to see what is happening inside the RL agent nets while training is running?

Some of my layers output NaN and I would like to know which one. I would also like to monitor to outputs of each layer.

Thanks in advance!
NicolasIs there any way to enter debug mode, to see what is happening inside the RL agent nets while training is running?

Some of my layers output NaN and I would like to know which one. I would also like to monitor to outputs of each layer.

Thanks in advance!
Nicolas Is there any way to enter debug mode, to see what is happening inside the RL agent nets while training is running?

Some of my layers output NaN and I would like to know which one. I would also like to monitor to outputs of each layer.

Thanks in advance!
Nicolas reinforcement learning, matlab, deep learning, debug mode MATLAB Answers — New Questions

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I have a gradient problem that involves the following function: adding a phase to each column in a matrix and computing the FFT of each column, and aggregating all FFTs into a new matrix.

My brute-force numerical gradient is adding a small phase to each column, iteratively, and then computing the loss by comparing it with some known matrix. currX is the current guess of phases, Ts2pHH is the matrix to whose columns these phases are added, and the function is computing by taking a sum along 2 dimensions of the intensity and then adding it up.
I want to know if this can be done more efficiently, because for my matrix size (~1000×1000) this takes around 2 minutes, which is very slow.
My code is shown below:
for k = 1:length(currX)
currX_perturbed = currX;
currX_perturbed(k) = currX_perturbed(k) + epsilon;
phases_perturbed = exp(1i * [0, currX_perturbed]);
Tcorr_perturbed = Ts2pHH .* phases_perturbed;
TcorrFFT_perturbed = fftshift(fft(fft(fft(fft(reshape(Tcorr_perturbed, [Npx, Npx, Nin, Nin]), [], 3), [], 4), [], 1), [], 2));
inputFreq_perturbed = squeeze(sum(sum(abs(TcorrFFT_perturbed).^2, 1), 2));
gradient(k) = gradient(k) + (-sum(inputFreq_perturbed .* support, ‘all’) – loss) / epsilon;
endI have a gradient problem that involves the following function: adding a phase to each column in a matrix and computing the FFT of each column, and aggregating all FFTs into a new matrix.

My brute-force numerical gradient is adding a small phase to each column, iteratively, and then computing the loss by comparing it with some known matrix. currX is the current guess of phases, Ts2pHH is the matrix to whose columns these phases are added, and the function is computing by taking a sum along 2 dimensions of the intensity and then adding it up.
I want to know if this can be done more efficiently, because for my matrix size (~1000×1000) this takes around 2 minutes, which is very slow.
My code is shown below:
for k = 1:length(currX)
currX_perturbed = currX;
currX_perturbed(k) = currX_perturbed(k) + epsilon;
phases_perturbed = exp(1i * [0, currX_perturbed]);
Tcorr_perturbed = Ts2pHH .* phases_perturbed;
TcorrFFT_perturbed = fftshift(fft(fft(fft(fft(reshape(Tcorr_perturbed, [Npx, Npx, Nin, Nin]), [], 3), [], 4), [], 1), [], 2));
inputFreq_perturbed = squeeze(sum(sum(abs(TcorrFFT_perturbed).^2, 1), 2));
gradient(k) = gradient(k) + (-sum(inputFreq_perturbed .* support, ‘all’) – loss) / epsilon;
end I have a gradient problem that involves the following function: adding a phase to each column in a matrix and computing the FFT of each column, and aggregating all FFTs into a new matrix.

My brute-force numerical gradient is adding a small phase to each column, iteratively, and then computing the loss by comparing it with some known matrix. currX is the current guess of phases, Ts2pHH is the matrix to whose columns these phases are added, and the function is computing by taking a sum along 2 dimensions of the intensity and then adding it up.
I want to know if this can be done more efficiently, because for my matrix size (~1000×1000) this takes around 2 minutes, which is very slow.
My code is shown below:
for k = 1:length(currX)
currX_perturbed = currX;
currX_perturbed(k) = currX_perturbed(k) + epsilon;
phases_perturbed = exp(1i * [0, currX_perturbed]);
Tcorr_perturbed = Ts2pHH .* phases_perturbed;
TcorrFFT_perturbed = fftshift(fft(fft(fft(fft(reshape(Tcorr_perturbed, [Npx, Npx, Nin, Nin]), [], 3), [], 4), [], 1), [], 2));
inputFreq_perturbed = squeeze(sum(sum(abs(TcorrFFT_perturbed).^2, 1), 2));
gradient(k) = gradient(k) + (-sum(inputFreq_perturbed .* support, ‘all’) – loss) / epsilon;
end gradient, optimization, speed, fft, for loop, matrix, loop, iteration MATLAB Answers — New Questions

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attached the screen shotattached the screen shot attached the screen shot #matfile conversion #tifformat MATLAB Answers — New Questions

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read(fds)
ans =
struct with fields:
data: {178093×3 cell}

Cell data is somthing like that
{1×1×9 double} {10×20×3 single} {[0.4343]}
How can extract all rows and but 1 and 3 number columns such as only {1×1×9 double} {[0.4343]} using fds.data ?read(fds)
ans =
struct with fields:
data: {178093×3 cell}

Cell data is somthing like that
{1×1×9 double} {10×20×3 single} {[0.4343]}
How can extract all rows and but 1 and 3 number columns such as only {1×1×9 double} {[0.4343]} using fds.data ? read(fds)
ans =
struct with fields:
data: {178093×3 cell}

Cell data is somthing like that
{1×1×9 double} {10×20×3 single} {[0.4343]}
How can extract all rows and but 1 and 3 number columns such as only {1×1×9 double} {[0.4343]} using fds.data ? filedatastore, cell MATLAB Answers — New Questions

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When I tried to update to R2024a, I got the popup to agree the license agreement. But I can’t click either "Yes" or "No", neither "Next" or "Cancel" button, like the screen shot attached below. I tried change screen resolution but it doesn’t resolve the issue. Any suggestions on how to solve it?

Many thanks!When I tried to update to R2024a, I got the popup to agree the license agreement. But I can’t click either "Yes" or "No", neither "Next" or "Cancel" button, like the screen shot attached below. I tried change screen resolution but it doesn’t resolve the issue. Any suggestions on how to solve it?

Many thanks! When I tried to update to R2024a, I got the popup to agree the license agreement. But I can’t click either "Yes" or "No", neither "Next" or "Cancel" button, like the screen shot attached below. I tried change screen resolution but it doesn’t resolve the issue. Any suggestions on how to solve it?

Many thanks! r2024a, update MATLAB Answers — New Questions

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Hey All

As the title suggests, I am dealing with a GUIDE file from a long time ago and I need to have it running and while its running I want to be able to access one of the functions called SaveSpectrumPlotButton_Callback() on line 1933

I have not been able to find how to access it from a different file or even create an output that I could maybe access in order to activate that button. I have shared the m file below

Any help would be much appreciated/Hey All

As the title suggests, I am dealing with a GUIDE file from a long time ago and I need to have it running and while its running I want to be able to access one of the functions called SaveSpectrumPlotButton_Callback() on line 1933

I have not been able to find how to access it from a different file or even create an output that I could maybe access in order to activate that button. I have shared the m file below

Any help would be much appreciated/ Hey All

As the title suggests, I am dealing with a GUIDE file from a long time ago and I need to have it running and while its running I want to be able to access one of the functions called SaveSpectrumPlotButton_Callback() on line 1933

I have not been able to find how to access it from a different file or even create an output that I could maybe access in order to activate that button. I have shared the m file below

Any help would be much appreciated/ guide, serial communication, functions MATLAB Answers — New Questions

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