Every time getting error In an assignment A(:) = B, the number of elements in A and B must be the same. while simulating circuit in MATLAB simullink while simulating circuit in MATLAB simulink
Kindly reslove the issue as early as possibleEvery time getting error In an assignment A(:) = B, the number of elements in A and B must be the same. while simulating circuit in MATLAB simullink while simulating circuit in MATLAB simulink
Kindly reslove the issue as early as possible Every time getting error In an assignment A(:) = B, the number of elements in A and B must be the same. while simulating circuit in MATLAB simullink while simulating circuit in MATLAB simulink
Kindly reslove the issue as early as possible simulink MATLAB Answers — New Questions

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Using 2016b, I need to measure pulse timings from a standard Simulink scope. It does not seem to be possible to select and drag them using the mouse.
The keyboard commands don’t seem to work either.Using 2016b, I need to measure pulse timings from a standard Simulink scope. It does not seem to be possible to select and drag them using the mouse.
The keyboard commands don’t seem to work either. Using 2016b, I need to measure pulse timings from a standard Simulink scope. It does not seem to be possible to select and drag them using the mouse.
The keyboard commands don’t seem to work either. scope, cursor MATLAB Answers — New Questions

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Greetings,

I’d like to know if it is possible to add up the cumulative sum from the values in a particular column that comply with the rule of being part of unique combinations of two ore more columns.

Please find below a simple sample code that could serve as illustration.

T = table({‘John’;’Mary’;’John’;’Mary’;’John’;’John’;’Mary’;’John’},…
{‘Lot A’;’Lot A’;’Lot A’;’Lot Z’;’Lot Z’;’Lot A’;’Lot Z’; ‘Lot Z’},…
datetime({’01/07/2015′;’03/08/2015′;’05/25/2014′;’03/26/2016′;’07/08/2009′;…
’03/01/2020′;’08/23/2010′;’06/15/2008′}),[12; 25; 36; 89; 11; 56; 87; 93],…
‘VariableNames’, {‘Salesperson’,’Lot’,’Date’,’Quantity’});

I’d like to know if I can produce a table that would return the cumulative sum of four possible unique combinations that are derived from the "Salesperson" and the "Lot" columns:

John – Lot A, John – Lot Z, Mary – Lot A, Mary – Lot Z

I’d like a table that would merge and add the cumulative sum of what John sold from Lot A, what John sold from Lot Z, what Mary sold from Lot A and what Mary sold from lot Z, which are the only four possible unique combinations derived from Columns 1 & 2 ("Salesperson & Lot").

As for the date, I’d like this solution to be able to include the date column. I know that the date is not part of the inputs required to derive this cumulative sum, but I’d like each unique combinations to include either the earliest or latest date.

Thank you in advance for your help.Greetings,

I’d like to know if it is possible to add up the cumulative sum from the values in a particular column that comply with the rule of being part of unique combinations of two ore more columns.

Please find below a simple sample code that could serve as illustration.

T = table({‘John’;’Mary’;’John’;’Mary’;’John’;’John’;’Mary’;’John’},…
{‘Lot A’;’Lot A’;’Lot A’;’Lot Z’;’Lot Z’;’Lot A’;’Lot Z’; ‘Lot Z’},…
datetime({’01/07/2015′;’03/08/2015′;’05/25/2014′;’03/26/2016′;’07/08/2009′;…
’03/01/2020′;’08/23/2010′;’06/15/2008′}),[12; 25; 36; 89; 11; 56; 87; 93],…
‘VariableNames’, {‘Salesperson’,’Lot’,’Date’,’Quantity’});

I’d like to know if I can produce a table that would return the cumulative sum of four possible unique combinations that are derived from the "Salesperson" and the "Lot" columns:

John – Lot A, John – Lot Z, Mary – Lot A, Mary – Lot Z

I’d like a table that would merge and add the cumulative sum of what John sold from Lot A, what John sold from Lot Z, what Mary sold from Lot A and what Mary sold from lot Z, which are the only four possible unique combinations derived from Columns 1 & 2 ("Salesperson & Lot").

As for the date, I’d like this solution to be able to include the date column. I know that the date is not part of the inputs required to derive this cumulative sum, but I’d like each unique combinations to include either the earliest or latest date.

Thank you in advance for your help. Greetings,

I’d like to know if it is possible to add up the cumulative sum from the values in a particular column that comply with the rule of being part of unique combinations of two ore more columns.

Please find below a simple sample code that could serve as illustration.

T = table({‘John’;’Mary’;’John’;’Mary’;’John’;’John’;’Mary’;’John’},…
{‘Lot A’;’Lot A’;’Lot A’;’Lot Z’;’Lot Z’;’Lot A’;’Lot Z’; ‘Lot Z’},…
datetime({’01/07/2015′;’03/08/2015′;’05/25/2014′;’03/26/2016′;’07/08/2009′;…
’03/01/2020′;’08/23/2010′;’06/15/2008′}),[12; 25; 36; 89; 11; 56; 87; 93],…
‘VariableNames’, {‘Salesperson’,’Lot’,’Date’,’Quantity’});

I’d like to know if I can produce a table that would return the cumulative sum of four possible unique combinations that are derived from the "Salesperson" and the "Lot" columns:

John – Lot A, John – Lot Z, Mary – Lot A, Mary – Lot Z

I’d like a table that would merge and add the cumulative sum of what John sold from Lot A, what John sold from Lot Z, what Mary sold from Lot A and what Mary sold from lot Z, which are the only four possible unique combinations derived from Columns 1 & 2 ("Salesperson & Lot").

As for the date, I’d like this solution to be able to include the date column. I know that the date is not part of the inputs required to derive this cumulative sum, but I’d like each unique combinations to include either the earliest or latest date.

Thank you in advance for your help. unique, accumarray, table MATLAB Answers — New Questions

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I want to perform Gaussian filtering on an image, but the size of the filter will continue to increase as the program progresses, while the image is getting smaller and smaller. This inevitably leads to a situation where the image size is smaller than the filter size. So, I used these two functions to give a simple example to see if they can work properly.

Now that the execution has ended, I find that the results of the two functions are not the same. I would like to ask if these two functions have different ways of handling the issue of exceeding the matrix boundary? And which function would be more recommended for Gaussian filtering of images in image processing?
a = [1 2 1; 2 1 2; 1 2 1];
% imgaussfilt函数滤波对于边界像素的处理
b = imgaussfilt(a, 1.6);
disp(b);

% 使用same约束矩阵大小，对边界像素的处理
sigma = 1.6;
size = 9;
gaussian_kernel = fspecial(‘gaussian’, size, sigma);
% disp(gaussian_kernel);
c = conv2(a, gaussian_kernel, ‘same’);
disp(c);I want to perform Gaussian filtering on an image, but the size of the filter will continue to increase as the program progresses, while the image is getting smaller and smaller. This inevitably leads to a situation where the image size is smaller than the filter size. So, I used these two functions to give a simple example to see if they can work properly.

Now that the execution has ended, I find that the results of the two functions are not the same. I would like to ask if these two functions have different ways of handling the issue of exceeding the matrix boundary? And which function would be more recommended for Gaussian filtering of images in image processing?
a = [1 2 1; 2 1 2; 1 2 1];
% imgaussfilt函数滤波对于边界像素的处理
b = imgaussfilt(a, 1.6);
disp(b);

% 使用same约束矩阵大小，对边界像素的处理
sigma = 1.6;
size = 9;
gaussian_kernel = fspecial(‘gaussian’, size, sigma);
% disp(gaussian_kernel);
c = conv2(a, gaussian_kernel, ‘same’);
disp(c); I want to perform Gaussian filtering on an image, but the size of the filter will continue to increase as the program progresses, while the image is getting smaller and smaller. This inevitably leads to a situation where the image size is smaller than the filter size. So, I used these two functions to give a simple example to see if they can work properly.

Now that the execution has ended, I find that the results of the two functions are not the same. I would like to ask if these two functions have different ways of handling the issue of exceeding the matrix boundary? And which function would be more recommended for Gaussian filtering of images in image processing?
a = [1 2 1; 2 1 2; 1 2 1];
% imgaussfilt函数滤波对于边界像素的处理
b = imgaussfilt(a, 1.6);
disp(b);

% 使用same约束矩阵大小，对边界像素的处理
sigma = 1.6;
size = 9;
gaussian_kernel = fspecial(‘gaussian’, size, sigma);
% disp(gaussian_kernel);
c = conv2(a, gaussian_kernel, ‘same’);
disp(c); fspecial，imgaussfilt，gauss，filter MATLAB Answers — New Questions

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I have X which is a 258×6 double and y which is a 258×1 double. These are used to fit a model utilizing fitlm. I found the quadratic to yield the best results.
X = outTableNumeric{:, corr_ids}; % Using the most correlated features
y = outTableNumeric.target; % Target variabel
% Fit a linear regression model
mdl = fitlm(X, y, "quadratic");
However when I try to derive a formula to be deployed outside matlab I find it extremely obscure how I’m to combine the quadratic terms with the coefficients and so on?

I tried to make the formula programmatically but that is not working when I test the result on some row of X.
coefficients = mdl.Coefficients.Estimate;
% Extract the simple notation of the formula
intercept = coefficients(1);
formula = sprintf(‘%.2f’, intercept);
for i = 2:length(coefficients)
if coefficients(i) ~= 0
feature_indices = find(strcmp(mdl.CoefficientNames, mdl.CoefficientNames{i}));
feature_name = mdl.CoefficientNames{feature_indices(1)};
formula = sprintf(‘%s + %.2f * %s’, formula, coefficients(i), feature_name);
end
end
strrep(formula,’:’,’*’);
disp(‘Simple notation of the formula:’);
disp(formula);
Can you please help me extract the full equation?I have X which is a 258×6 double and y which is a 258×1 double. These are used to fit a model utilizing fitlm. I found the quadratic to yield the best results.
X = outTableNumeric{:, corr_ids}; % Using the most correlated features
y = outTableNumeric.target; % Target variabel
% Fit a linear regression model
mdl = fitlm(X, y, "quadratic");
However when I try to derive a formula to be deployed outside matlab I find it extremely obscure how I’m to combine the quadratic terms with the coefficients and so on?

I tried to make the formula programmatically but that is not working when I test the result on some row of X.
coefficients = mdl.Coefficients.Estimate;
% Extract the simple notation of the formula
intercept = coefficients(1);
formula = sprintf(‘%.2f’, intercept);
for i = 2:length(coefficients)
if coefficients(i) ~= 0
feature_indices = find(strcmp(mdl.CoefficientNames, mdl.CoefficientNames{i}));
feature_name = mdl.CoefficientNames{feature_indices(1)};
formula = sprintf(‘%s + %.2f * %s’, formula, coefficients(i), feature_name);
end
end
strrep(formula,’:’,’*’);
disp(‘Simple notation of the formula:’);
disp(formula);
Can you please help me extract the full equation? I have X which is a 258×6 double and y which is a 258×1 double. These are used to fit a model utilizing fitlm. I found the quadratic to yield the best results.
X = outTableNumeric{:, corr_ids}; % Using the most correlated features
y = outTableNumeric.target; % Target variabel
% Fit a linear regression model
mdl = fitlm(X, y, "quadratic");
However when I try to derive a formula to be deployed outside matlab I find it extremely obscure how I’m to combine the quadratic terms with the coefficients and so on?

I tried to make the formula programmatically but that is not working when I test the result on some row of X.
coefficients = mdl.Coefficients.Estimate;
% Extract the simple notation of the formula
intercept = coefficients(1);
formula = sprintf(‘%.2f’, intercept);
for i = 2:length(coefficients)
if coefficients(i) ~= 0
feature_indices = find(strcmp(mdl.CoefficientNames, mdl.CoefficientNames{i}));
feature_name = mdl.CoefficientNames{feature_indices(1)};
formula = sprintf(‘%s + %.2f * %s’, formula, coefficients(i), feature_name);
end
end
strrep(formula,’:’,’*’);
disp(‘Simple notation of the formula:’);
disp(formula);
Can you please help me extract the full equation? #fitlm MATLAB Answers — New Questions

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hello i need to run simulink simulation from matlab, how to do it using matlab command in script ?hello i need to run simulink simulation from matlab, how to do it using matlab command in script ? hello i need to run simulink simulation from matlab, how to do it using matlab command in script ? simulink, run function MATLAB Answers — New Questions

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I am trying to run my simulink model in parallel while saving the results to a matfile after each simulation has completed.
Each worker should take the following action:
Simulate model with simIn( j )
Create matfile for above simulation
Repeate with simIn ( K ) until all simulations are complete.

The below code is my starting point. "test_model" is a simulink model of only a sin wave going into a gain, integrator, and to workspace block simply to test out parsim().

%% Example of how to run simulink models in parallel
clear; close all; clc;

mdl = "test_model";
amp= 1:10;
freq = 1:10;

nSims = length(amp);
simIn(1:nSims) = Simulink.SimulationInput(mdl);

% Setup model workspace
k = 5;

for i =1:nSims
nm = [num2str(i) ‘.mat’];

simIn(i) = setVariable(simIn(i), "amp", amp(i), ‘Workspace’, mdl);
simIn(i) = setVariable(simIn(i), "freq", freq(i), ‘Workspace’, mdl);
simIn(i) = setPostSimFcn(simIn(i), @(x)postSim(x, simIn(i), nm));

end

out = parsim (simIn, ‘UseFastRestart’,’on’, ‘TransferBaseWorkspaceVariables’,’on’);

function postSim(out, in, nm)
% postSim – Run @ completion of each simulation
% Saves simulation input, output, and name to file "nm"
m = matfile(nm, ‘Writable’, true);
m.out = out;
m.in = in;
m.nm = nm;
end

I understand that save() does not work as expected in parallel, so I’ve implemented the example from the question below as a method of creating my mat files. The above code works exactly as expected if "parsim" is replaced with "sim"; however, no files are created when using "parsim".
https://www.mathworks.com/matlabcentral/answers/135285-how-do-i-use-save-with-a-parfor-loop-using-parallel-computing-toolbox

Note: setting ‘TransferBaseWorkspaceVariables’ to ‘off’ and setting k via setVariable does not have any impact on this behavior.

Ask: How can I modify the above code to also work with the parsim command?I am trying to run my simulink model in parallel while saving the results to a matfile after each simulation has completed.
Each worker should take the following action:
Simulate model with simIn( j )
Create matfile for above simulation
Repeate with simIn ( K ) until all simulations are complete.

The below code is my starting point. "test_model" is a simulink model of only a sin wave going into a gain, integrator, and to workspace block simply to test out parsim().

%% Example of how to run simulink models in parallel
clear; close all; clc;

mdl = "test_model";
amp= 1:10;
freq = 1:10;

nSims = length(amp);
simIn(1:nSims) = Simulink.SimulationInput(mdl);

% Setup model workspace
k = 5;

for i =1:nSims
nm = [num2str(i) ‘.mat’];

simIn(i) = setVariable(simIn(i), "amp", amp(i), ‘Workspace’, mdl);
simIn(i) = setVariable(simIn(i), "freq", freq(i), ‘Workspace’, mdl);
simIn(i) = setPostSimFcn(simIn(i), @(x)postSim(x, simIn(i), nm));

end

out = parsim (simIn, ‘UseFastRestart’,’on’, ‘TransferBaseWorkspaceVariables’,’on’);

function postSim(out, in, nm)
% postSim – Run @ completion of each simulation
% Saves simulation input, output, and name to file "nm"
m = matfile(nm, ‘Writable’, true);
m.out = out;
m.in = in;
m.nm = nm;
end

I understand that save() does not work as expected in parallel, so I’ve implemented the example from the question below as a method of creating my mat files. The above code works exactly as expected if "parsim" is replaced with "sim"; however, no files are created when using "parsim".
https://www.mathworks.com/matlabcentral/answers/135285-how-do-i-use-save-with-a-parfor-loop-using-parallel-computing-toolbox

Note: setting ‘TransferBaseWorkspaceVariables’ to ‘off’ and setting k via setVariable does not have any impact on this behavior.

Ask: How can I modify the above code to also work with the parsim command? I am trying to run my simulink model in parallel while saving the results to a matfile after each simulation has completed.
Each worker should take the following action:
Simulate model with simIn( j )
Create matfile for above simulation
Repeate with simIn ( K ) until all simulations are complete.

The below code is my starting point. "test_model" is a simulink model of only a sin wave going into a gain, integrator, and to workspace block simply to test out parsim().

%% Example of how to run simulink models in parallel
clear; close all; clc;

mdl = "test_model";
amp= 1:10;
freq = 1:10;

nSims = length(amp);
simIn(1:nSims) = Simulink.SimulationInput(mdl);

% Setup model workspace
k = 5;

for i =1:nSims
nm = [num2str(i) ‘.mat’];

simIn(i) = setVariable(simIn(i), "amp", amp(i), ‘Workspace’, mdl);
simIn(i) = setVariable(simIn(i), "freq", freq(i), ‘Workspace’, mdl);
simIn(i) = setPostSimFcn(simIn(i), @(x)postSim(x, simIn(i), nm));

end

out = parsim (simIn, ‘UseFastRestart’,’on’, ‘TransferBaseWorkspaceVariables’,’on’);

function postSim(out, in, nm)
% postSim – Run @ completion of each simulation
% Saves simulation input, output, and name to file "nm"
m = matfile(nm, ‘Writable’, true);
m.out = out;
m.in = in;
m.nm = nm;
end

I understand that save() does not work as expected in parallel, so I’ve implemented the example from the question below as a method of creating my mat files. The above code works exactly as expected if "parsim" is replaced with "sim"; however, no files are created when using "parsim".
https://www.mathworks.com/matlabcentral/answers/135285-how-do-i-use-save-with-a-parfor-loop-using-parallel-computing-toolbox

Note: setting ‘TransferBaseWorkspaceVariables’ to ‘off’ and setting k via setVariable does not have any impact on this behavior.

Ask: How can I modify the above code to also work with the parsim command? simulink, parallel computing toolbox MATLAB Answers — New Questions

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I am having a struct data type that consists of 2000 different names of places with their avg temperatures . When I open the struct variable I get a huge list. How can I quickly locate the variable and read its values without scrolling down to every variable. I don’t see any find option in the window. One may say I can code it. Yes, I can do that but I am looking for alternative quick ways so that I don’t need to write the code to find it.I am having a struct data type that consists of 2000 different names of places with their avg temperatures . When I open the struct variable I get a huge list. How can I quickly locate the variable and read its values without scrolling down to every variable. I don’t see any find option in the window. One may say I can code it. Yes, I can do that but I am looking for alternative quick ways so that I don’t need to write the code to find it. I am having a struct data type that consists of 2000 different names of places with their avg temperatures . When I open the struct variable I get a huge list. How can I quickly locate the variable and read its values without scrolling down to every variable. I don’t see any find option in the window. One may say I can code it. Yes, I can do that but I am looking for alternative quick ways so that I don’t need to write the code to find it. quick variable search in struct variable window MATLAB Answers — New Questions

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I have a 578×235 grid of ocean temperature data in which the land pixels are NaN. I would like to create a 1 pixel buffer around the coastline so that all pixels adjacent to an existing NaN also become NaN. I’m unsure on the best way to do this. I thought I could create a logical array of NaNs and not NaNs but am not sure on the best way to extract a polygon and create the buffer after that step.I have a 578×235 grid of ocean temperature data in which the land pixels are NaN. I would like to create a 1 pixel buffer around the coastline so that all pixels adjacent to an existing NaN also become NaN. I’m unsure on the best way to do this. I thought I could create a logical array of NaNs and not NaNs but am not sure on the best way to extract a polygon and create the buffer after that step. I have a 578×235 grid of ocean temperature data in which the land pixels are NaN. I would like to create a 1 pixel buffer around the coastline so that all pixels adjacent to an existing NaN also become NaN. I’m unsure on the best way to do this. I thought I could create a logical array of NaNs and not NaNs but am not sure on the best way to extract a polygon and create the buffer after that step. extract polygon, buffer MATLAB Answers — New Questions

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How do I plot similar cross quantile correlation plotHow do I plot similar cross quantile correlation plot How do I plot similar cross quantile correlation plot heatmap, quantile, correlat MATLAB Answers — New Questions

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