Hello,
I have 12 CSV files from a chromatic confocal sensor.
Each file has three columns: x, y, z.
The problem:
Each measurement has different x,y and z positions, since it is spirally scanning. I found x is more deviating than y and z.
I want to create a virtual reference surface by averaging these 12 measurements.
To do that, I need to interpolate each dataset onto the same (x,y) grid before averaging.
My questions:
How can I load all 10 CSVs and interpolate them onto a common regular grid in MATLAB?
2. What is the best function for interpolation in this case (griddata, scatteredInterpolant, or something else)?
3. Once all are on the same grid, how do I average the z-values to get one final reference surface and save it as a CSV?
Any example code or workflow would be greatly appreciated.
Thanks in advance!Hello,
I have 12 CSV files from a chromatic confocal sensor.
Each file has three columns: x, y, z.
The problem:
Each measurement has different x,y and z positions, since it is spirally scanning. I found x is more deviating than y and z.
I want to create a virtual reference surface by averaging these 12 measurements.
To do that, I need to interpolate each dataset onto the same (x,y) grid before averaging.
My questions:
How can I load all 10 CSVs and interpolate them onto a common regular grid in MATLAB?
2. What is the best function for interpolation in this case (griddata, scatteredInterpolant, or something else)?
3. Once all are on the same grid, how do I average the z-values to get one final reference surface and save it as a CSV?
Any example code or workflow would be greatly appreciated.
Thanks in advance! Hello,
I have 12 CSV files from a chromatic confocal sensor.
Each file has three columns: x, y, z.
The problem:
Each measurement has different x,y and z positions, since it is spirally scanning. I found x is more deviating than y and z.
I want to create a virtual reference surface by averaging these 12 measurements.
To do that, I need to interpolate each dataset onto the same (x,y) grid before averaging.
My questions:
How can I load all 10 CSVs and interpolate them onto a common regular grid in MATLAB?
2. What is the best function for interpolation in this case (griddata, scatteredInterpolant, or something else)?
3. Once all are on the same grid, how do I average the z-values to get one final reference surface and save it as a CSV?
Any example code or workflow would be greatly appreciated.
Thanks in advance! interpolation, averaging, csv, combine MATLAB Answers — New Questions

​

Hello,
I am using Embedded Coder with the ERT TLC file to generate C code from Simulink models.
I would like to know if it is possible to configure the code generator so that the generated functions and source files comply with the Google C Style Guide.
In particular, I am interested in:
Function naming conventions
Indentation and formatting rules
File structure and organization
Is there any built-in support for this, or would it require customizing TLC files and code generation templates?
Any references or examples would be very helpful.
Thank you in advance!Hello,
I am using Embedded Coder with the ERT TLC file to generate C code from Simulink models.
I would like to know if it is possible to configure the code generator so that the generated functions and source files comply with the Google C Style Guide.
In particular, I am interested in:
Function naming conventions
Indentation and formatting rules
File structure and organization
Is there any built-in support for this, or would it require customizing TLC files and code generation templates?
Any references or examples would be very helpful.
Thank you in advance! Hello,
I am using Embedded Coder with the ERT TLC file to generate C code from Simulink models.
I would like to know if it is possible to configure the code generator so that the generated functions and source files comply with the Google C Style Guide.
In particular, I am interested in:
Function naming conventions
Indentation and formatting rules
File structure and organization
Is there any built-in support for this, or would it require customizing TLC files and code generation templates?
Any references or examples would be very helpful.
Thank you in advance! embedded coder, google style, standard MATLAB Answers — New Questions

​

Hello all, I have a weird issue I was wondering if someone might have some idea on how to fix. I’m running Matlab 2024b on a Dell XPS 14 laptop. My issue is that seemingly randomly (perhaps 1 out every 6-10 operations) Matlab takes forever to run selected lines of code (or anything at all). For instance, I just ran this line of code:
tic
ECR_PBO_Support_1 = [];
ECR_PBO_Support_2 = [norm_2_32_PBO_Support01.ECR, norm_2_32_PBO_Support02.ECR, norm_2_32_PBO_Support03.ECR, norm_2_32_PBO_Support04.ECR, norm_2_32_PBO_Support05.ECR,…
norm_2_32_PBO_Support06.ECR, norm_2_32_PBO_Support07.ECR, norm_2_32_PBO_Support08.ECR];
ECR_PBO_Support_Total = [ECR_PBO_Support_1,ECR_PBO_Support_2];
toc
What the data is is irrelevant (its ultimately 8 vectors of 100 numbers long). But when I ran these lines, Matlab took about 5-8 seconds to run (i.e. it displays ‘Busy". Even though the output of tic toc was:
Elapsed time is 0.015314 seconds.
For the life of me, I cannot figure out why Matlab is doing this, but its causing me to really slow down since even the most basic operations will randomly take 5-8 seconds to run. When it happens, the delay affects everything, calculations, plots etc.
Has anyone experienced this before or have any suggestions for settings to check?Hello all, I have a weird issue I was wondering if someone might have some idea on how to fix. I’m running Matlab 2024b on a Dell XPS 14 laptop. My issue is that seemingly randomly (perhaps 1 out every 6-10 operations) Matlab takes forever to run selected lines of code (or anything at all). For instance, I just ran this line of code:
tic
ECR_PBO_Support_1 = [];
ECR_PBO_Support_2 = [norm_2_32_PBO_Support01.ECR, norm_2_32_PBO_Support02.ECR, norm_2_32_PBO_Support03.ECR, norm_2_32_PBO_Support04.ECR, norm_2_32_PBO_Support05.ECR,…
norm_2_32_PBO_Support06.ECR, norm_2_32_PBO_Support07.ECR, norm_2_32_PBO_Support08.ECR];
ECR_PBO_Support_Total = [ECR_PBO_Support_1,ECR_PBO_Support_2];
toc
What the data is is irrelevant (its ultimately 8 vectors of 100 numbers long). But when I ran these lines, Matlab took about 5-8 seconds to run (i.e. it displays ‘Busy". Even though the output of tic toc was:
Elapsed time is 0.015314 seconds.
For the life of me, I cannot figure out why Matlab is doing this, but its causing me to really slow down since even the most basic operations will randomly take 5-8 seconds to run. When it happens, the delay affects everything, calculations, plots etc.
Has anyone experienced this before or have any suggestions for settings to check? Hello all, I have a weird issue I was wondering if someone might have some idea on how to fix. I’m running Matlab 2024b on a Dell XPS 14 laptop. My issue is that seemingly randomly (perhaps 1 out every 6-10 operations) Matlab takes forever to run selected lines of code (or anything at all). For instance, I just ran this line of code:
tic
ECR_PBO_Support_1 = [];
ECR_PBO_Support_2 = [norm_2_32_PBO_Support01.ECR, norm_2_32_PBO_Support02.ECR, norm_2_32_PBO_Support03.ECR, norm_2_32_PBO_Support04.ECR, norm_2_32_PBO_Support05.ECR,…
norm_2_32_PBO_Support06.ECR, norm_2_32_PBO_Support07.ECR, norm_2_32_PBO_Support08.ECR];
ECR_PBO_Support_Total = [ECR_PBO_Support_1,ECR_PBO_Support_2];
toc
What the data is is irrelevant (its ultimately 8 vectors of 100 numbers long). But when I ran these lines, Matlab took about 5-8 seconds to run (i.e. it displays ‘Busy". Even though the output of tic toc was:
Elapsed time is 0.015314 seconds.
For the life of me, I cannot figure out why Matlab is doing this, but its causing me to really slow down since even the most basic operations will randomly take 5-8 seconds to run. When it happens, the delay affects everything, calculations, plots etc.
Has anyone experienced this before or have any suggestions for settings to check? processing time, matlab, script, speed, optimization MATLAB Answers — New Questions

​

MATLAB has commands such as ispc/ismac/isunix and computer to determine the local computing environment. Is there a way to distinguish MATLAB Online and MATLAB Mobile from a local install? Both the online and mobile versions report themselves as 64-bit Linux, which is presumably the Mathworks server running behind the scenes. Both also have an enviroment variable MW_DDUX_APP_NAME that does not appear on Mac or Windows installs, with the very telling value MATLAB_ONLINE. My assumption is that a local Linux install would not have that variable, and if a local server did, the value would be different (unless one was running MATLAB Online behind a firewall).
So far I haven’t found a simple way of separating online and mobile versions, apart from a try/catch block containing a command that does not work on the latter (such as uifigure). That’s not very robust–is there a better way?MATLAB has commands such as ispc/ismac/isunix and computer to determine the local computing environment. Is there a way to distinguish MATLAB Online and MATLAB Mobile from a local install? Both the online and mobile versions report themselves as 64-bit Linux, which is presumably the Mathworks server running behind the scenes. Both also have an enviroment variable MW_DDUX_APP_NAME that does not appear on Mac or Windows installs, with the very telling value MATLAB_ONLINE. My assumption is that a local Linux install would not have that variable, and if a local server did, the value would be different (unless one was running MATLAB Online behind a firewall).
So far I haven’t found a simple way of separating online and mobile versions, apart from a try/catch block containing a command that does not work on the latter (such as uifigure). That’s not very robust–is there a better way? MATLAB has commands such as ispc/ismac/isunix and computer to determine the local computing environment. Is there a way to distinguish MATLAB Online and MATLAB Mobile from a local install? Both the online and mobile versions report themselves as 64-bit Linux, which is presumably the Mathworks server running behind the scenes. Both also have an enviroment variable MW_DDUX_APP_NAME that does not appear on Mac or Windows installs, with the very telling value MATLAB_ONLINE. My assumption is that a local Linux install would not have that variable, and if a local server did, the value would be different (unless one was running MATLAB Online behind a firewall).
So far I haven’t found a simple way of separating online and mobile versions, apart from a try/catch block containing a command that does not work on the latter (such as uifigure). That’s not very robust–is there a better way? online, mobile MATLAB Answers — New Questions

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I am trying to remove detected circles that are too close to one another. My original plan involved indexing through all of the centers (X Y stored in separate columns), determining the distances, and then using those to remove points within a tolerance.
for nn=1:height(location_table)
distances=sqrt(((location_table(nn,1) – location_table(:,1)).^2)+((location_table(nn,2) – location_table(:,2)).^2))
too_close=(0<distances & distances<tolerance);
location_table(too_close,:)=[]
end
I was never able to get the removal to work. It would end up breaking if spots were removed because the index nn would eventually get larger than the current table height.
I discovered the uniquetol command when searching for answers. However, in my use of it, it filters out spots that are not unique (ie, within the tolerance). However, I would want it to remove spots that all spots that are too similar (rather than leaving a representative one behind).
location_table=uniquetol(location_table, closeness_tolerance, ‘ByRows’, true, ‘OutputAllIndices’, true, ‘DataScale’,1);
I plan to do radial intensity line scans starting at the center of all circles (and proceeding past their perimeter by a variable) that make it through this filtering process. If spots are too close, then the scan (improfile) will cross over the border of the intended scan as well as a spot that is too close to it (which will skew the data). For example, circle 4 should be excluded because it is too close to other circles and its scans could be skewed. Uniquetold allowed me to exclude the nearby circles but 4 would ideally not be included either.I am trying to remove detected circles that are too close to one another. My original plan involved indexing through all of the centers (X Y stored in separate columns), determining the distances, and then using those to remove points within a tolerance.
for nn=1:height(location_table)
distances=sqrt(((location_table(nn,1) – location_table(:,1)).^2)+((location_table(nn,2) – location_table(:,2)).^2))
too_close=(0<distances & distances<tolerance);
location_table(too_close,:)=[]
end
I was never able to get the removal to work. It would end up breaking if spots were removed because the index nn would eventually get larger than the current table height.
I discovered the uniquetol command when searching for answers. However, in my use of it, it filters out spots that are not unique (ie, within the tolerance). However, I would want it to remove spots that all spots that are too similar (rather than leaving a representative one behind).
location_table=uniquetol(location_table, closeness_tolerance, ‘ByRows’, true, ‘OutputAllIndices’, true, ‘DataScale’,1);
I plan to do radial intensity line scans starting at the center of all circles (and proceeding past their perimeter by a variable) that make it through this filtering process. If spots are too close, then the scan (improfile) will cross over the border of the intended scan as well as a spot that is too close to it (which will skew the data). For example, circle 4 should be excluded because it is too close to other circles and its scans could be skewed. Uniquetold allowed me to exclude the nearby circles but 4 would ideally not be included either. I am trying to remove detected circles that are too close to one another. My original plan involved indexing through all of the centers (X Y stored in separate columns), determining the distances, and then using those to remove points within a tolerance.
for nn=1:height(location_table)
distances=sqrt(((location_table(nn,1) – location_table(:,1)).^2)+((location_table(nn,2) – location_table(:,2)).^2))
too_close=(0<distances & distances<tolerance);
location_table(too_close,:)=[]
end
I was never able to get the removal to work. It would end up breaking if spots were removed because the index nn would eventually get larger than the current table height.
I discovered the uniquetol command when searching for answers. However, in my use of it, it filters out spots that are not unique (ie, within the tolerance). However, I would want it to remove spots that all spots that are too similar (rather than leaving a representative one behind).
location_table=uniquetol(location_table, closeness_tolerance, ‘ByRows’, true, ‘OutputAllIndices’, true, ‘DataScale’,1);
I plan to do radial intensity line scans starting at the center of all circles (and proceeding past their perimeter by a variable) that make it through this filtering process. If spots are too close, then the scan (improfile) will cross over the border of the intended scan as well as a spot that is too close to it (which will skew the data). For example, circle 4 should be excluded because it is too close to other circles and its scans could be skewed. Uniquetold allowed me to exclude the nearby circles but 4 would ideally not be included either. uniquetol, image analysis, image processing MATLAB Answers — New Questions

​

I have the following constrained (global) optimization problem:
For a user defined sorted real values vector:
xi = [xi(1), … , xi(N+1)]
I need to find unknown vector:
x = [x(1), …, x(L)]
where the integer L is the unknown length of the vector x (L>=0, L = 0 is the trivial case)
and the unknown vector x = [x(1), …, x(L)] must satisfy the following specific conditions:
===============================================================
0. The new "refined" sorted vector xo = union(xi,x), where length(xo) = L+N+1
should to fulfil the following set of conditions:
1. min(xo) = xo(1) = xi(1), max(xo) = xo(L+N+1) = xi(N+1)
2a. max(z(j)/z(j+1),z(j+1)/z(j)) < q_max, for j = 1, 2, … L+N
2b. max(z(j-1)/z(j),z(j)/z(j-1)) < q_max, for j = 2, 2, … L+N+1
where
z(j) = xo(j+1) – xo(j) , z = diff(xo), length(z) = L+N
and
q_max is user defined max ratio, where q_max > 1 (typically q_max ~ 1.05 – 1.2)
3. min(z) -> maximal, minimal distance between xo vector elements should be maximized.
It is obvious that for small L the constraint conditions (2) is not possible to satisfy.

===============================================================

The motivation of this problem is the creation of the so called, "homogenized" 1-D grid, where consecutive distances between elements of vector xo are relatively "slowly" changing.

I will be very happy for any recommendation how to effectively solve this problem using MATLAB + (global) optimization toolbox.I have the following constrained (global) optimization problem:
For a user defined sorted real values vector:
xi = [xi(1), … , xi(N+1)]
I need to find unknown vector:
x = [x(1), …, x(L)]
where the integer L is the unknown length of the vector x (L>=0, L = 0 is the trivial case)
and the unknown vector x = [x(1), …, x(L)] must satisfy the following specific conditions:
===============================================================
0. The new "refined" sorted vector xo = union(xi,x), where length(xo) = L+N+1
should to fulfil the following set of conditions:
1. min(xo) = xo(1) = xi(1), max(xo) = xo(L+N+1) = xi(N+1)
2a. max(z(j)/z(j+1),z(j+1)/z(j)) < q_max, for j = 1, 2, … L+N
2b. max(z(j-1)/z(j),z(j)/z(j-1)) < q_max, for j = 2, 2, … L+N+1
where
z(j) = xo(j+1) – xo(j) , z = diff(xo), length(z) = L+N
and
q_max is user defined max ratio, where q_max > 1 (typically q_max ~ 1.05 – 1.2)
3. min(z) -> maximal, minimal distance between xo vector elements should be maximized.
It is obvious that for small L the constraint conditions (2) is not possible to satisfy.

===============================================================

The motivation of this problem is the creation of the so called, "homogenized" 1-D grid, where consecutive distances between elements of vector xo are relatively "slowly" changing.

I will be very happy for any recommendation how to effectively solve this problem using MATLAB + (global) optimization toolbox. I have the following constrained (global) optimization problem:
For a user defined sorted real values vector:
xi = [xi(1), … , xi(N+1)]
I need to find unknown vector:
x = [x(1), …, x(L)]
where the integer L is the unknown length of the vector x (L>=0, L = 0 is the trivial case)
and the unknown vector x = [x(1), …, x(L)] must satisfy the following specific conditions:
===============================================================
0. The new "refined" sorted vector xo = union(xi,x), where length(xo) = L+N+1
should to fulfil the following set of conditions:
1. min(xo) = xo(1) = xi(1), max(xo) = xo(L+N+1) = xi(N+1)
2a. max(z(j)/z(j+1),z(j+1)/z(j)) < q_max, for j = 1, 2, … L+N
2b. max(z(j-1)/z(j),z(j)/z(j-1)) < q_max, for j = 2, 2, … L+N+1
where
z(j) = xo(j+1) – xo(j) , z = diff(xo), length(z) = L+N
and
q_max is user defined max ratio, where q_max > 1 (typically q_max ~ 1.05 – 1.2)
3. min(z) -> maximal, minimal distance between xo vector elements should be maximized.
It is obvious that for small L the constraint conditions (2) is not possible to satisfy.

===============================================================

The motivation of this problem is the creation of the so called, "homogenized" 1-D grid, where consecutive distances between elements of vector xo are relatively "slowly" changing.

I will be very happy for any recommendation how to effectively solve this problem using MATLAB + (global) optimization toolbox. optmization, constrained MATLAB Answers — New Questions

​

Remove the dark spots on the leopard.
i tried converting the color image into grayscale.Applied ostu thresholding to create binary image.
using the morophological operations i was able to create a mask, used mask to refilll the black spots on the color image. i did not get the desired result.
what other steps i can implement to achieve an image with no black spotsRemove the dark spots on the leopard.
i tried converting the color image into grayscale.Applied ostu thresholding to create binary image.
using the morophological operations i was able to create a mask, used mask to refilll the black spots on the color image. i did not get the desired result.
what other steps i can implement to achieve an image with no black spots Remove the dark spots on the leopard.
i tried converting the color image into grayscale.Applied ostu thresholding to create binary image.
using the morophological operations i was able to create a mask, used mask to refilll the black spots on the color image. i did not get the desired result.
what other steps i can implement to achieve an image with no black spots image processing, image segmentation, hole filling MATLAB Answers — New Questions

​

Hi, does anyone know why there is so much whitespace after each entry in the legend here? I’ve tried to shrink the legend width by doing:
pos = legend.Position;
pos(3) = 0.5*pos(3);
legend.Position = pos;
But this hasn’t worked. I’ve attached the code below.
Any help would be appreciated.

Here is the code below: (I’m sure there is a better way to write the legend names out, but I’m lazy and this was good enough for my purposes).
f = figure;
hold on
plot(Cl, Cm(:,1),"-bsquare")
plot(Cl, Cm(:,3),"-bdiamond")
plot(Cl, Cm(:,5),"-b^")
plot(Cl, Cm(:,7),"-bv")
plot(Cl, Cm(:,2),"-rsquare")
plot(Cl, Cm(:,4),"-rdiamond")
plot(Cl, Cm(:,6),"-r^")
plot(Cl, Cm(:,8),"-rv")
hold off
xlim([-1.1, 1.4])
leg = legend({‘$x_{cg}=0.18bar{c}, delta_e = 0degree $’,’$x_{cg}=0.22bar{c}, delta_e = 0degree $’,’$x_{cg}=0.26bar{c}, delta_e = 0degree $’,’$x_{cg}=0.30bar{c}, delta_e = 0degree $’,’$x_{cg}=0.18bar{c}, delta_e = 5degree $’,’$x_{cg}=0.22bar{c}, delta_e = 5degree $’,’$x_{cg}=0.26bar{c}, delta_e = 5degree $’,’$x_{cg}=0.30bar{c}, delta_e = 5degree $’},’Interpreter’,’latex’, ‘Location’,’northeast’, ‘FontSize’,11);
% pos = leg.Position;
% pos(3) = 0.25*pos(3); % Tried this, didn’t work
% leg.Position = pos;
grid on
ax = gca;
ax.GridLineWidth = 1.5;
ax.XAxis.MinorTick = ‘on’;
ax.XMinorGrid = ‘on’;
ax.YAxis.MinorTick = ‘on’;
ax.YMinorGrid = ‘on’;
f.Units = ‘pixels’;
f.Position = [10,10,990,490];Hi, does anyone know why there is so much whitespace after each entry in the legend here? I’ve tried to shrink the legend width by doing:
pos = legend.Position;
pos(3) = 0.5*pos(3);
legend.Position = pos;
But this hasn’t worked. I’ve attached the code below.
Any help would be appreciated.

Here is the code below: (I’m sure there is a better way to write the legend names out, but I’m lazy and this was good enough for my purposes).
f = figure;
hold on
plot(Cl, Cm(:,1),"-bsquare")
plot(Cl, Cm(:,3),"-bdiamond")
plot(Cl, Cm(:,5),"-b^")
plot(Cl, Cm(:,7),"-bv")
plot(Cl, Cm(:,2),"-rsquare")
plot(Cl, Cm(:,4),"-rdiamond")
plot(Cl, Cm(:,6),"-r^")
plot(Cl, Cm(:,8),"-rv")
hold off
xlim([-1.1, 1.4])
leg = legend({‘$x_{cg}=0.18bar{c}, delta_e = 0degree $’,’$x_{cg}=0.22bar{c}, delta_e = 0degree $’,’$x_{cg}=0.26bar{c}, delta_e = 0degree $’,’$x_{cg}=0.30bar{c}, delta_e = 0degree $’,’$x_{cg}=0.18bar{c}, delta_e = 5degree $’,’$x_{cg}=0.22bar{c}, delta_e = 5degree $’,’$x_{cg}=0.26bar{c}, delta_e = 5degree $’,’$x_{cg}=0.30bar{c}, delta_e = 5degree $’},’Interpreter’,’latex’, ‘Location’,’northeast’, ‘FontSize’,11);
% pos = leg.Position;
% pos(3) = 0.25*pos(3); % Tried this, didn’t work
% leg.Position = pos;
grid on
ax = gca;
ax.GridLineWidth = 1.5;
ax.XAxis.MinorTick = ‘on’;
ax.XMinorGrid = ‘on’;
ax.YAxis.MinorTick = ‘on’;
ax.YMinorGrid = ‘on’;
f.Units = ‘pixels’;
f.Position = [10,10,990,490]; Hi, does anyone know why there is so much whitespace after each entry in the legend here? I’ve tried to shrink the legend width by doing:
pos = legend.Position;
pos(3) = 0.5*pos(3);
legend.Position = pos;
But this hasn’t worked. I’ve attached the code below.
Any help would be appreciated.

Here is the code below: (I’m sure there is a better way to write the legend names out, but I’m lazy and this was good enough for my purposes).
f = figure;
hold on
plot(Cl, Cm(:,1),"-bsquare")
plot(Cl, Cm(:,3),"-bdiamond")
plot(Cl, Cm(:,5),"-b^")
plot(Cl, Cm(:,7),"-bv")
plot(Cl, Cm(:,2),"-rsquare")
plot(Cl, Cm(:,4),"-rdiamond")
plot(Cl, Cm(:,6),"-r^")
plot(Cl, Cm(:,8),"-rv")
hold off
xlim([-1.1, 1.4])
leg = legend({‘$x_{cg}=0.18bar{c}, delta_e = 0degree $’,’$x_{cg}=0.22bar{c}, delta_e = 0degree $’,’$x_{cg}=0.26bar{c}, delta_e = 0degree $’,’$x_{cg}=0.30bar{c}, delta_e = 0degree $’,’$x_{cg}=0.18bar{c}, delta_e = 5degree $’,’$x_{cg}=0.22bar{c}, delta_e = 5degree $’,’$x_{cg}=0.26bar{c}, delta_e = 5degree $’,’$x_{cg}=0.30bar{c}, delta_e = 5degree $’},’Interpreter’,’latex’, ‘Location’,’northeast’, ‘FontSize’,11);
% pos = leg.Position;
% pos(3) = 0.25*pos(3); % Tried this, didn’t work
% leg.Position = pos;
grid on
ax = gca;
ax.GridLineWidth = 1.5;
ax.XAxis.MinorTick = ‘on’;
ax.XMinorGrid = ‘on’;
ax.YAxis.MinorTick = ‘on’;
ax.YMinorGrid = ‘on’;
f.Units = ‘pixels’;
f.Position = [10,10,990,490]; legend MATLAB Answers — New Questions

​