Hi,
I would like to estimate spatial frequency based on FFT from the attached image intensity data. The findpeaks() does the job though, but for some other reason I still need to find the frequency from FFT.Hi,
I would like to estimate spatial frequency based on FFT from the attached image intensity data. The findpeaks() does the job though, but for some other reason I still need to find the frequency from FFT. Hi,
I would like to estimate spatial frequency based on FFT from the attached image intensity data. The findpeaks() does the job though, but for some other reason I still need to find the frequency from FFT. fft, spatial frequency, image processing MATLAB Answers — New Questions

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You are designing a spherical tank as in the figure to hold water for your village V = n * h ^ 2 * [(3k – b)/3] 1- Show that the volume of liquid it can hold can be computed as where V volume [n]h depth of water in tank [m], and R the tank radius [m]

2. If R= 3 m, to what depth must the tank be filled so that it holds 30 m? Use the false- position method to determine your answer. Determine the approximate relative error

after each iteration. Employ initial guesses of 0 and RYou are designing a spherical tank as in the figure to hold water for your village V = n * h ^ 2 * [(3k – b)/3] 1- Show that the volume of liquid it can hold can be computed as where V volume [n]h depth of water in tank [m], and R the tank radius [m]

2. If R= 3 m, to what depth must the tank be filled so that it holds 30 m? Use the false- position method to determine your answer. Determine the approximate relative error

after each iteration. Employ initial guesses of 0 and R You are designing a spherical tank as in the figure to hold water for your village V = n * h ^ 2 * [(3k – b)/3] 1- Show that the volume of liquid it can hold can be computed as where V volume [n]h depth of water in tank [m], and R the tank radius [m]

2. If R= 3 m, to what depth must the tank be filled so that it holds 30 m? Use the false- position method to determine your answer. Determine the approximate relative error

after each iteration. Employ initial guesses of 0 and R #false-position MATLAB Answers — New Questions

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Hello,
I’m getting out of memory errors when trying to copy a large dataset (9003×9003 double) using Ctrl+C with the intention of pasting it to Excel, even though I’ve increased the Java Heap memory to the maximum. The error window suggests copying portions (I’m not doing that with such a large dataset) or exporting the dataset to a file – how do I do that please? I would expect such an option in its right-click menu but it’s not there – i.e. let’s make the paid software as complicated as we can :)))
xlswrite leaves me with empty files, csvwrite with corrupt files – even though it’s plain data
Thank youHello,
I’m getting out of memory errors when trying to copy a large dataset (9003×9003 double) using Ctrl+C with the intention of pasting it to Excel, even though I’ve increased the Java Heap memory to the maximum. The error window suggests copying portions (I’m not doing that with such a large dataset) or exporting the dataset to a file – how do I do that please? I would expect such an option in its right-click menu but it’s not there – i.e. let’s make the paid software as complicated as we can :)))
xlswrite leaves me with empty files, csvwrite with corrupt files – even though it’s plain data
Thank you Hello,
I’m getting out of memory errors when trying to copy a large dataset (9003×9003 double) using Ctrl+C with the intention of pasting it to Excel, even though I’ve increased the Java Heap memory to the maximum. The error window suggests copying portions (I’m not doing that with such a large dataset) or exporting the dataset to a file – how do I do that please? I would expect such an option in its right-click menu but it’s not there – i.e. let’s make the paid software as complicated as we can :)))
xlswrite leaves me with empty files, csvwrite with corrupt files – even though it’s plain data
Thank you matlab, export, excel, memory MATLAB Answers — New Questions

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Hello, I am trying to estimate the background of this image. One way I would like to try is to break the image up into small regions and take the minium value in each region and then peform a surface fit to these. The aim would be to then subtract this from my main image (one thing I definetly need is smoothness, i.e no sharp jumps between regions)
My raw image showing the regions

The min in each region is obtained via blockproc (data attached)
blockMin =
183.00 185.00 184.00 195.00 198.00 185.00 203.00
194.00 204.00 188.00 192.00 217.00 190.00 212.00
202.00 213.00 204.00 191.00 208.00 210.00 209.00
204.00 205.00 225.00 204.00 202.00 210.00 211.00
225.00 240.00 219.00 209.00 210.00 227.00 210.00
225.00 213.00 217.00 241.00 223.00 226.00 223.00
219.00 222.00 232.00 233.00 217.00 238.00 231.00

Very strangely, the heatmap and surf plot of the same data set is showing a difference (I know I must rotate the surf plot, but its clear the peak regions are in different positions (shown by green circles). On the heatmap, the value of 241 is on the 3rd row, yet on the surf plot its on the 2nd row and on the wrong column.

This is my code (Im showing the pure surf plot above, not the smoothdata2 version)
blockFwhm;
figure
h=heatmap(blockFwhm, ‘Colormap’,cool,’FontSize’,10); % app.PanelScan,
h.CellLabelFormat = ‘%.0f’;

figure
ax1=subplot(1,2,1); ax2=subplot(1,2,2);
surf(ax1,blockFwhm); colormap cool; colorbar

% Try to smotth the data *** Although this isn’t very good so
% far
B=smoothdata2(blockFwhm);
s=surf(ax2,B); colormap cool;Hello, I am trying to estimate the background of this image. One way I would like to try is to break the image up into small regions and take the minium value in each region and then peform a surface fit to these. The aim would be to then subtract this from my main image (one thing I definetly need is smoothness, i.e no sharp jumps between regions)
My raw image showing the regions

The min in each region is obtained via blockproc (data attached)
blockMin =
183.00 185.00 184.00 195.00 198.00 185.00 203.00
194.00 204.00 188.00 192.00 217.00 190.00 212.00
202.00 213.00 204.00 191.00 208.00 210.00 209.00
204.00 205.00 225.00 204.00 202.00 210.00 211.00
225.00 240.00 219.00 209.00 210.00 227.00 210.00
225.00 213.00 217.00 241.00 223.00 226.00 223.00
219.00 222.00 232.00 233.00 217.00 238.00 231.00

Very strangely, the heatmap and surf plot of the same data set is showing a difference (I know I must rotate the surf plot, but its clear the peak regions are in different positions (shown by green circles). On the heatmap, the value of 241 is on the 3rd row, yet on the surf plot its on the 2nd row and on the wrong column.

This is my code (Im showing the pure surf plot above, not the smoothdata2 version)
blockFwhm;
figure
h=heatmap(blockFwhm, ‘Colormap’,cool,’FontSize’,10); % app.PanelScan,
h.CellLabelFormat = ‘%.0f’;

figure
ax1=subplot(1,2,1); ax2=subplot(1,2,2);
surf(ax1,blockFwhm); colormap cool; colorbar

% Try to smotth the data *** Although this isn’t very good so
% far
B=smoothdata2(blockFwhm);
s=surf(ax2,B); colormap cool; Hello, I am trying to estimate the background of this image. One way I would like to try is to break the image up into small regions and take the minium value in each region and then peform a surface fit to these. The aim would be to then subtract this from my main image (one thing I definetly need is smoothness, i.e no sharp jumps between regions)
My raw image showing the regions

The min in each region is obtained via blockproc (data attached)
blockMin =
183.00 185.00 184.00 195.00 198.00 185.00 203.00
194.00 204.00 188.00 192.00 217.00 190.00 212.00
202.00 213.00 204.00 191.00 208.00 210.00 209.00
204.00 205.00 225.00 204.00 202.00 210.00 211.00
225.00 240.00 219.00 209.00 210.00 227.00 210.00
225.00 213.00 217.00 241.00 223.00 226.00 223.00
219.00 222.00 232.00 233.00 217.00 238.00 231.00

Very strangely, the heatmap and surf plot of the same data set is showing a difference (I know I must rotate the surf plot, but its clear the peak regions are in different positions (shown by green circles). On the heatmap, the value of 241 is on the 3rd row, yet on the surf plot its on the 2nd row and on the wrong column.

This is my code (Im showing the pure surf plot above, not the smoothdata2 version)
blockFwhm;
figure
h=heatmap(blockFwhm, ‘Colormap’,cool,’FontSize’,10); % app.PanelScan,
h.CellLabelFormat = ‘%.0f’;

figure
ax1=subplot(1,2,1); ax2=subplot(1,2,2);
surf(ax1,blockFwhm); colormap cool; colorbar

% Try to smotth the data *** Although this isn’t very good so
% far
B=smoothdata2(blockFwhm);
s=surf(ax2,B); colormap cool; image, heatmap, surf, smoothdata2 MATLAB Answers — New Questions

​

Hei. I am beginner of Mablab, today (04/19/2025, helsinki time), I played around the Matlab 2025a )pre-release(, what i want to do was to visualize the ‘mpg’ dataset in R. The example figure is like below:

What i got with Matlab 2025a was like:

as youcan see, the coclor bar is looks strange. So, I swithched to Matlab 2024b with same script. And i got:

colormap is back to normal now. So, i was thinking some thing happends in Matlab2025a, which i don’t know.
Code (colormap from ‘200 colormap ‘ add-on):
mpg = readtable(‘mpg.csv’);
mpg.class = categorical(mpg.class);
fig = figure;
fig.Position = [100, 100, 800, 300]; % [left, bottom, width, height];
% we need transfor the class column as catereory variable
mpg.class = categorical(mpg.class);

fig = figure;
fig.Position = [100, 100, 800, 300]; % [left, bottom, width, height]
clp = slanCM("538",7);
t = tiledlayout(1,2);
ax1 = nexttile;
scatter(mpg.displ,mpg.hwy,[],mpg.class,’filled’)

colormap(clp);
colorbar(‘TickLabels’, cellstr(unique(mpg.class)));

ax2 = nexttile;
gscatter(mpg.displ,mpg.hwy,mpg.class,[],’+o*.xsd’)
legend(‘Location’,’eastoutside’)
axs = [ax1;ax2];
for i = 1:2
set(axs(i), ‘FontSize’, 12, ‘FontName’, ‘Times New Roman’);
axs(i).XLim = [0 8];
grid(axs(i),’on’)
end
t.TileSpacing = ‘compact’;
t.XLabel.String = ‘Disp’;
t.YLabel.String = ‘Hwy’;
t.XLabel.FontName = ‘Times New Roman’;
t.YLabel.FontName = ‘Times New Roman’;Hei. I am beginner of Mablab, today (04/19/2025, helsinki time), I played around the Matlab 2025a )pre-release(, what i want to do was to visualize the ‘mpg’ dataset in R. The example figure is like below:

What i got with Matlab 2025a was like:

as youcan see, the coclor bar is looks strange. So, I swithched to Matlab 2024b with same script. And i got:

colormap is back to normal now. So, i was thinking some thing happends in Matlab2025a, which i don’t know.
Code (colormap from ‘200 colormap ‘ add-on):
mpg = readtable(‘mpg.csv’);
mpg.class = categorical(mpg.class);
fig = figure;
fig.Position = [100, 100, 800, 300]; % [left, bottom, width, height];
% we need transfor the class column as catereory variable
mpg.class = categorical(mpg.class);

fig = figure;
fig.Position = [100, 100, 800, 300]; % [left, bottom, width, height]
clp = slanCM("538",7);
t = tiledlayout(1,2);
ax1 = nexttile;
scatter(mpg.displ,mpg.hwy,[],mpg.class,’filled’)

colormap(clp);
colorbar(‘TickLabels’, cellstr(unique(mpg.class)));

ax2 = nexttile;
gscatter(mpg.displ,mpg.hwy,mpg.class,[],’+o*.xsd’)
legend(‘Location’,’eastoutside’)
axs = [ax1;ax2];
for i = 1:2
set(axs(i), ‘FontSize’, 12, ‘FontName’, ‘Times New Roman’);
axs(i).XLim = [0 8];
grid(axs(i),’on’)
end
t.TileSpacing = ‘compact’;
t.XLabel.String = ‘Disp’;
t.YLabel.String = ‘Hwy’;
t.XLabel.FontName = ‘Times New Roman’;
t.YLabel.FontName = ‘Times New Roman’; Hei. I am beginner of Mablab, today (04/19/2025, helsinki time), I played around the Matlab 2025a )pre-release(, what i want to do was to visualize the ‘mpg’ dataset in R. The example figure is like below:

What i got with Matlab 2025a was like:

as youcan see, the coclor bar is looks strange. So, I swithched to Matlab 2024b with same script. And i got:

colormap is back to normal now. So, i was thinking some thing happends in Matlab2025a, which i don’t know.
Code (colormap from ‘200 colormap ‘ add-on):
mpg = readtable(‘mpg.csv’);
mpg.class = categorical(mpg.class);
fig = figure;
fig.Position = [100, 100, 800, 300]; % [left, bottom, width, height];
% we need transfor the class column as catereory variable
mpg.class = categorical(mpg.class);

fig = figure;
fig.Position = [100, 100, 800, 300]; % [left, bottom, width, height]
clp = slanCM("538",7);
t = tiledlayout(1,2);
ax1 = nexttile;
scatter(mpg.displ,mpg.hwy,[],mpg.class,’filled’)

colormap(clp);
colorbar(‘TickLabels’, cellstr(unique(mpg.class)));

ax2 = nexttile;
gscatter(mpg.displ,mpg.hwy,mpg.class,[],’+o*.xsd’)
legend(‘Location’,’eastoutside’)
axs = [ax1;ax2];
for i = 1:2
set(axs(i), ‘FontSize’, 12, ‘FontName’, ‘Times New Roman’);
axs(i).XLim = [0 8];
grid(axs(i),’on’)
end
t.TileSpacing = ‘compact’;
t.XLabel.String = ‘Disp’;
t.YLabel.String = ‘Hwy’;
t.XLabel.FontName = ‘Times New Roman’;
t.YLabel.FontName = ‘Times New Roman’; 2025a, pre-release, plot, scatter, colorer MATLAB Answers — New Questions

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I’m using the pde toolbox to solve a certain elliptic equation in 2D.

Solution is fine, although I do need to plot it along a given line, i.e. to cut a planar slice from the 3D mesh representing the solution.

I can’t figure out a way that smartly involves the toolbox functions.

Any help appreciated.I’m using the pde toolbox to solve a certain elliptic equation in 2D.

Solution is fine, although I do need to plot it along a given line, i.e. to cut a planar slice from the 3D mesh representing the solution.

I can’t figure out a way that smartly involves the toolbox functions.

Any help appreciated. I’m using the pde toolbox to solve a certain elliptic equation in 2D.

Solution is fine, although I do need to plot it along a given line, i.e. to cut a planar slice from the 3D mesh representing the solution.

I can’t figure out a way that smartly involves the toolbox functions.

Any help appreciated. pde toolbox, plot, pde, plotting MATLAB Answers — New Questions

​

Hi,

I have a table in Matlab with many rows. I can copy from Matlab and paste into Excel.
But the headers are gone. How to copy the headers into Excel as well?
Thanks for any help.

JZHi,

I have a table in Matlab with many rows. I can copy from Matlab and paste into Excel.
But the headers are gone. How to copy the headers into Excel as well?
Thanks for any help.

JZ Hi,

I have a table in Matlab with many rows. I can copy from Matlab and paste into Excel.
But the headers are gone. How to copy the headers into Excel as well?
Thanks for any help.

JZ matlab MATLAB Answers — New Questions

​

I have the following data coming from a stochastic experiment. I ran the experiment for 10 times for each x and tabulated the mean and standard deviations. How can I use both the mean and standard deviation to train a surrogate model? I tried using fitrgp but it does not take standard deviations. I could use sigma, but it takes a scaler value, not a vector.
x = [5; 7; 9; 11; 13];

mean_output= [103.78; 108.84; 117.68; 109.57; 72.26];
std_output = [4.20; 3.44; 4.25; 10.09; 10.71];

gprModels = fitrgp(x, mean_output, …
‘KernelFunction’, ‘squaredexponential’, …
‘BasisFunction’, ‘constant’, …
‘FitMethod’, ‘exact’, …
‘PredictMethod’, ‘exact’)I have the following data coming from a stochastic experiment. I ran the experiment for 10 times for each x and tabulated the mean and standard deviations. How can I use both the mean and standard deviation to train a surrogate model? I tried using fitrgp but it does not take standard deviations. I could use sigma, but it takes a scaler value, not a vector.
x = [5; 7; 9; 11; 13];

mean_output= [103.78; 108.84; 117.68; 109.57; 72.26];
std_output = [4.20; 3.44; 4.25; 10.09; 10.71];

gprModels = fitrgp(x, mean_output, …
‘KernelFunction’, ‘squaredexponential’, …
‘BasisFunction’, ‘constant’, …
‘FitMethod’, ‘exact’, …
‘PredictMethod’, ‘exact’) I have the following data coming from a stochastic experiment. I ran the experiment for 10 times for each x and tabulated the mean and standard deviations. How can I use both the mean and standard deviation to train a surrogate model? I tried using fitrgp but it does not take standard deviations. I could use sigma, but it takes a scaler value, not a vector.
x = [5; 7; 9; 11; 13];

mean_output= [103.78; 108.84; 117.68; 109.57; 72.26];
std_output = [4.20; 3.44; 4.25; 10.09; 10.71];

gprModels = fitrgp(x, mean_output, …
‘KernelFunction’, ‘squaredexponential’, …
‘BasisFunction’, ‘constant’, …
‘FitMethod’, ‘exact’, …
‘PredictMethod’, ‘exact’) surrogate, fitrgp MATLAB Answers — New Questions

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