Hi there,
I am implementing a conjugate gradient based optimisation algorithm, and to achieve this i need to calculate the grad of the input function. I currently pass in an anonymous function, which is comprised as the sum of other anonymous functions, of which those are comprised of standard matlab functions. Here is how the objective function is defined
% one constraint for example – all 6 are similar form
c2 = @(x) mat.minSF_yield – mat.yield …
/ axial_stress(mat.F, mat.E, x(1), x(2));

transf_obj = @(x) obj(x) – r * (1 / (c1(x) + c2(x) + c3(x) + c4(x) + c5(x) + c6(x)));

the partial derivative function calculates the partial derivative anon functions and adds them into a cell. This allows the partials to be calculated before the optimisation loop saving computation time
function [grad_cell] = partials(func, x)
% Get dimensionality of inputs
n = numel(x);

% Convert the anonymous function to a symbolic expression
syms a [1 n]
funcSym = func(a);

% Initialize the array to hold partial derivative functions
grad_vect = zeros(1, n);

grad_cell = cell(1,n);
% Compute partial derivatives
for i = 1:n
% Compute symbolic partial derivative with respect to the i-th variable
partialDerivSym = diff(funcSym, a(i));

% Convert symbolic partial derivative back to an anon function
grad = matlabFunction(partialDerivSym, ‘Vars’, {a});

% Add anon function to cell
grad_cell{i} = grad;
end
end
To evalute the gradient at a specific point the following function is used
function [nabla] = compute_grad(cell, x)
nabla = zeros(1,numel(x))
for i =1:numel(x)
nabla(i) = cell{i}(x);
end
end
When evaluting any partial, for some values such as x = [14,3] something within the feasable domain, an empty array is returned. And for values such as x=[7.9,7], a value close to the results i was getting from using fmincon an error of the following is produced.
Error using diff
Difference order N must be a positive integer scalar.
Error in sym/matlabFunction>@(in1)(in1(:,1).*pi.*(3.0./2.5e+…
My current theory is that the conversion to and from symbolic variables to compute the derivative is not being achieved successfuly given the combination of anon functions and locally defined functions. I have tested the partials function with simple functions directly defined and it appears to work. This program is split across 3 files, the first which defines variables and calls the conj-grad m-file. This file then calls the partials.m file which is just the partials function.
%% Variable Definition …
…
%% Call ‘Conj_grad.m’
%% Call ‘partials.m’
%% Returns cell
%% compute at specific point, indexing from cell using compute_grad function
%% Error

Any help is much appreciated.Hi there,
I am implementing a conjugate gradient based optimisation algorithm, and to achieve this i need to calculate the grad of the input function. I currently pass in an anonymous function, which is comprised as the sum of other anonymous functions, of which those are comprised of standard matlab functions. Here is how the objective function is defined
% one constraint for example – all 6 are similar form
c2 = @(x) mat.minSF_yield – mat.yield …
/ axial_stress(mat.F, mat.E, x(1), x(2));

transf_obj = @(x) obj(x) – r * (1 / (c1(x) + c2(x) + c3(x) + c4(x) + c5(x) + c6(x)));

the partial derivative function calculates the partial derivative anon functions and adds them into a cell. This allows the partials to be calculated before the optimisation loop saving computation time
function [grad_cell] = partials(func, x)
% Get dimensionality of inputs
n = numel(x);

% Convert the anonymous function to a symbolic expression
syms a [1 n]
funcSym = func(a);

% Initialize the array to hold partial derivative functions
grad_vect = zeros(1, n);

grad_cell = cell(1,n);
% Compute partial derivatives
for i = 1:n
% Compute symbolic partial derivative with respect to the i-th variable
partialDerivSym = diff(funcSym, a(i));

% Convert symbolic partial derivative back to an anon function
grad = matlabFunction(partialDerivSym, ‘Vars’, {a});

% Add anon function to cell
grad_cell{i} = grad;
end
end
To evalute the gradient at a specific point the following function is used
function [nabla] = compute_grad(cell, x)
nabla = zeros(1,numel(x))
for i =1:numel(x)
nabla(i) = cell{i}(x);
end
end
When evaluting any partial, for some values such as x = [14,3] something within the feasable domain, an empty array is returned. And for values such as x=[7.9,7], a value close to the results i was getting from using fmincon an error of the following is produced.
Error using diff
Difference order N must be a positive integer scalar.
Error in sym/matlabFunction>@(in1)(in1(:,1).*pi.*(3.0./2.5e+…
My current theory is that the conversion to and from symbolic variables to compute the derivative is not being achieved successfuly given the combination of anon functions and locally defined functions. I have tested the partials function with simple functions directly defined and it appears to work. This program is split across 3 files, the first which defines variables and calls the conj-grad m-file. This file then calls the partials.m file which is just the partials function.
%% Variable Definition …
…
%% Call ‘Conj_grad.m’
%% Call ‘partials.m’
%% Returns cell
%% compute at specific point, indexing from cell using compute_grad function
%% Error

Any help is much appreciated. Hi there,
I am implementing a conjugate gradient based optimisation algorithm, and to achieve this i need to calculate the grad of the input function. I currently pass in an anonymous function, which is comprised as the sum of other anonymous functions, of which those are comprised of standard matlab functions. Here is how the objective function is defined
% one constraint for example – all 6 are similar form
c2 = @(x) mat.minSF_yield – mat.yield …
/ axial_stress(mat.F, mat.E, x(1), x(2));

transf_obj = @(x) obj(x) – r * (1 / (c1(x) + c2(x) + c3(x) + c4(x) + c5(x) + c6(x)));

the partial derivative function calculates the partial derivative anon functions and adds them into a cell. This allows the partials to be calculated before the optimisation loop saving computation time
function [grad_cell] = partials(func, x)
% Get dimensionality of inputs
n = numel(x);

% Convert the anonymous function to a symbolic expression
syms a [1 n]
funcSym = func(a);

% Initialize the array to hold partial derivative functions
grad_vect = zeros(1, n);

grad_cell = cell(1,n);
% Compute partial derivatives
for i = 1:n
% Compute symbolic partial derivative with respect to the i-th variable
partialDerivSym = diff(funcSym, a(i));

% Convert symbolic partial derivative back to an anon function
grad = matlabFunction(partialDerivSym, ‘Vars’, {a});

% Add anon function to cell
grad_cell{i} = grad;
end
end
To evalute the gradient at a specific point the following function is used
function [nabla] = compute_grad(cell, x)
nabla = zeros(1,numel(x))
for i =1:numel(x)
nabla(i) = cell{i}(x);
end
end
When evaluting any partial, for some values such as x = [14,3] something within the feasable domain, an empty array is returned. And for values such as x=[7.9,7], a value close to the results i was getting from using fmincon an error of the following is produced.
Error using diff
Difference order N must be a positive integer scalar.
Error in sym/matlabFunction>@(in1)(in1(:,1).*pi.*(3.0./2.5e+…
My current theory is that the conversion to and from symbolic variables to compute the derivative is not being achieved successfuly given the combination of anon functions and locally defined functions. I have tested the partials function with simple functions directly defined and it appears to work. This program is split across 3 files, the first which defines variables and calls the conj-grad m-file. This file then calls the partials.m file which is just the partials function.
%% Variable Definition …
…
%% Call ‘Conj_grad.m’
%% Call ‘partials.m’
%% Returns cell
%% compute at specific point, indexing from cell using compute_grad function
%% Error

Any help is much appreciated. anonymous functions, partial derivatives MATLAB Answers — New Questions

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Hello Friends,

I have a .mat file loaded in workspace. I want to convert it into .csv file. It has real entries. I used to convert it before using the following commands without any problem:

M = dlmread(‘FileName.mat’, ‘t’, 1, 0);
csvwrite(‘FileName.csv’, M)

But now something is wrong with MATLAB. My dataset is the same. Nothing has changed, but now it gives the following error:

Error using dlmread (line 139)
Mismatch between file and format string.
Trouble reading number from file (row 1u, field 1u) ==>
}Ûa�&Ír!ÃþxbSo�Èñæo8k:¬i’³*Y#�~!I�jË9B¯Ý�WG~
¬zN=å0ɁÀo8Ó’Rå@õR[iãY>,xÊ8UrVÀ9ó";~~�ÀOWAe$�Æ:xfnFVAÿñ�ϼÓЪÍða�þn

I wonder if MATLAB changed something with dlmwrite function! Please advise.Hello Friends,

I have a .mat file loaded in workspace. I want to convert it into .csv file. It has real entries. I used to convert it before using the following commands without any problem:

M = dlmread(‘FileName.mat’, ‘t’, 1, 0);
csvwrite(‘FileName.csv’, M)

But now something is wrong with MATLAB. My dataset is the same. Nothing has changed, but now it gives the following error:

Error using dlmread (line 139)
Mismatch between file and format string.
Trouble reading number from file (row 1u, field 1u) ==>
}Ûa�&Ír!ÃþxbSo�Èñæo8k:¬i’³*Y#�~!I�jË9B¯Ý�WG~
¬zN=å0ɁÀo8Ó’Rå@õR[iãY>,xÊ8UrVÀ9ó";~~�ÀOWAe$�Æ:xfnFVAÿñ�ϼÓЪÍða�þn

I wonder if MATLAB changed something with dlmwrite function! Please advise. Hello Friends,

I have a .mat file loaded in workspace. I want to convert it into .csv file. It has real entries. I used to convert it before using the following commands without any problem:

M = dlmread(‘FileName.mat’, ‘t’, 1, 0);
csvwrite(‘FileName.csv’, M)

But now something is wrong with MATLAB. My dataset is the same. Nothing has changed, but now it gives the following error:

Error using dlmread (line 139)
Mismatch between file and format string.
Trouble reading number from file (row 1u, field 1u) ==>
}Ûa�&Ír!ÃþxbSo�Èñæo8k:¬i’³*Y#�~!I�jË9B¯Ý�WG~
¬zN=å0ɁÀo8Ó’Rå@õR[iãY>,xÊ8UrVÀ9ó";~~�ÀOWAe$�Æ:xfnFVAÿñ�ϼÓЪÍða�þn

I wonder if MATLAB changed something with dlmwrite function! Please advise. dlmwrite, csvwrite, csvread, mat, csv, .mat, .csv, .dat, convert from .mat to .csv, error MATLAB Answers — New Questions

​

Hello,
I am analysing EEG data using a code that was provided to me. This bit of code was working well a year ago, and I am using it now to add new datasets.I don’t understand what has changed that make it throw an error now.
The script below is used to average, plot and display the 93 EEG electrodes accross all trials for all participants. I get the following error:
Index in position 2 exceeds array bounds (must not exceed 175).
Error in butterfly_graph (line 8)
data_STD(:,:,i) = DATA{1,i}.avg(:, 1:350);

DATA is stored in a file called DataForCluster_allparticipants.mat. I don’t understand what exactly is the index in position 2 that exceeds array bounds. I apologise if the answer is very obvious.
my scripts can be found here: https://we.tl/t-0ozTcZFgex
DataForCluster_allparticipants.mat that is the file where the DATA variable is stored
The script forLucie_loadDataForCluster.mat is the script generating the DATA file
The script Butterfly_graph is the script in which I have a problem
load(‘DataForCluster_allparticipants.mat’)
cd(‘/Users/dan/Documents/LucieEEG/Analysis/Sorted’) %change this
%d(1,:) is standard
%d(2,:) is deviant
% d(3,:) is MMN

for i = 1:length(DATA)
data_STD(:,:,i) = DATA{1,i}.avg(:, 1:350);
data_DEV(:,:,i) = DATA{2,i}.avg(:, 1:350);
data_MMN(:,:,i) = DATA{3,i}.avg(:, 1:350);
endHello,
I am analysing EEG data using a code that was provided to me. This bit of code was working well a year ago, and I am using it now to add new datasets.I don’t understand what has changed that make it throw an error now.
The script below is used to average, plot and display the 93 EEG electrodes accross all trials for all participants. I get the following error:
Index in position 2 exceeds array bounds (must not exceed 175).
Error in butterfly_graph (line 8)
data_STD(:,:,i) = DATA{1,i}.avg(:, 1:350);

DATA is stored in a file called DataForCluster_allparticipants.mat. I don’t understand what exactly is the index in position 2 that exceeds array bounds. I apologise if the answer is very obvious.
my scripts can be found here: https://we.tl/t-0ozTcZFgex
DataForCluster_allparticipants.mat that is the file where the DATA variable is stored
The script forLucie_loadDataForCluster.mat is the script generating the DATA file
The script Butterfly_graph is the script in which I have a problem
load(‘DataForCluster_allparticipants.mat’)
cd(‘/Users/dan/Documents/LucieEEG/Analysis/Sorted’) %change this
%d(1,:) is standard
%d(2,:) is deviant
% d(3,:) is MMN

for i = 1:length(DATA)
data_STD(:,:,i) = DATA{1,i}.avg(:, 1:350);
data_DEV(:,:,i) = DATA{2,i}.avg(:, 1:350);
data_MMN(:,:,i) = DATA{3,i}.avg(:, 1:350);
end Hello,
I am analysing EEG data using a code that was provided to me. This bit of code was working well a year ago, and I am using it now to add new datasets.I don’t understand what has changed that make it throw an error now.
The script below is used to average, plot and display the 93 EEG electrodes accross all trials for all participants. I get the following error:
Index in position 2 exceeds array bounds (must not exceed 175).
Error in butterfly_graph (line 8)
data_STD(:,:,i) = DATA{1,i}.avg(:, 1:350);

DATA is stored in a file called DataForCluster_allparticipants.mat. I don’t understand what exactly is the index in position 2 that exceeds array bounds. I apologise if the answer is very obvious.
my scripts can be found here: https://we.tl/t-0ozTcZFgex
DataForCluster_allparticipants.mat that is the file where the DATA variable is stored
The script forLucie_loadDataForCluster.mat is the script generating the DATA file
The script Butterfly_graph is the script in which I have a problem
load(‘DataForCluster_allparticipants.mat’)
cd(‘/Users/dan/Documents/LucieEEG/Analysis/Sorted’) %change this
%d(1,:) is standard
%d(2,:) is deviant
% d(3,:) is MMN

for i = 1:length(DATA)
data_STD(:,:,i) = DATA{1,i}.avg(:, 1:350);
data_DEV(:,:,i) = DATA{2,i}.avg(:, 1:350);
data_MMN(:,:,i) = DATA{3,i}.avg(:, 1:350);
end psychology, eeg, indexing MATLAB Answers — New Questions

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