grid on
xlabel(‘X’)
ylabel(‘Y’)
zlabel(‘Z’)
title([‘Tiempo de ‘,num2str(t(i)),’s’],’FontSize’,18)
axis([-60,60,-60,60,0,60])
legend(‘Eslabón 1′,’Eslabón 2′,’Eslabón 3′,’Eslabón 4′,’FontSize’,16)
dim = ([0.8 0.4 0.1 0.2])
annotation(‘textbox’,dim,’String’,num2str([‘Vcm1′,’Vcm2′,’Vcm3′,’Vcm4’]), ‘FontSize’;15) Invalid expression.
view(100,35)
pause(0.01)grid on
xlabel(‘X’)
ylabel(‘Y’)
zlabel(‘Z’)
title([‘Tiempo de ‘,num2str(t(i)),’s’],’FontSize’,18)
axis([-60,60,-60,60,0,60])
legend(‘Eslabón 1′,’Eslabón 2′,’Eslabón 3′,’Eslabón 4′,’FontSize’,16)
dim = ([0.8 0.4 0.1 0.2])
annotation(‘textbox’,dim,’String’,num2str([‘Vcm1′,’Vcm2′,’Vcm3′,’Vcm4’]), ‘FontSize’;15) Invalid expression.
view(100,35)
pause(0.01) grid on
xlabel(‘X’)
ylabel(‘Y’)
zlabel(‘Z’)
title([‘Tiempo de ‘,num2str(t(i)),’s’],’FontSize’,18)
axis([-60,60,-60,60,0,60])
legend(‘Eslabón 1′,’Eslabón 2′,’Eslabón 3′,’Eslabón 4′,’FontSize’,16)
dim = ([0.8 0.4 0.1 0.2])
annotation(‘textbox’,dim,’String’,num2str([‘Vcm1′,’Vcm2′,’Vcm3′,’Vcm4’]), ‘FontSize’;15) Invalid expression.
view(100,35)
pause(0.01) vcm, num2str MATLAB Answers — New Questions

​

And, What is the difference between using delay and not using it when estimating a path for ANC?
The filter will already cause significant delay, so should I use it?

Thank you for your interest!
https://kr.mathworks.com/help/audio/ug/active-noise-control-with-simulink.htmlAnd, What is the difference between using delay and not using it when estimating a path for ANC?
The filter will already cause significant delay, so should I use it?

Thank you for your interest!
https://kr.mathworks.com/help/audio/ug/active-noise-control-with-simulink.html And, What is the difference between using delay and not using it when estimating a path for ANC?
The filter will already cause significant delay, so should I use it?

Thank you for your interest!
https://kr.mathworks.com/help/audio/ug/active-noise-control-with-simulink.html anc, fir, simulink MATLAB Answers — New Questions

​

I made a simulink spice model for a circuit and it is taking around 30 minutes to compile, I thought it was normal, but checking windows task manager it seems that only one thread of my cpu is at it’s maximum capacity, i tried using different configurations of workers and threads per worker, but nothing work it is still using arount 21% of the total of my CPU.
My simulink model has only one .slx
I am using this code for the parallel computing part
bdclose all;
%proj = openProject(‘.C:UsersfernaDownloadshalfBridgeTest.slx’);
model = ‘DownloadshalfBridgeTest.slx’;
open_system(model);

modelN = ‘halfBridgeTest’;
in = Simulink.SimulationInput(modelN);

parpool(‘LocalProfile1’)
tic; out = parsim(in, ‘UseFastRestart’,’on’); toc

delete(gcp(‘nocreate’));I made a simulink spice model for a circuit and it is taking around 30 minutes to compile, I thought it was normal, but checking windows task manager it seems that only one thread of my cpu is at it’s maximum capacity, i tried using different configurations of workers and threads per worker, but nothing work it is still using arount 21% of the total of my CPU.
My simulink model has only one .slx
I am using this code for the parallel computing part
bdclose all;
%proj = openProject(‘.C:UsersfernaDownloadshalfBridgeTest.slx’);
model = ‘DownloadshalfBridgeTest.slx’;
open_system(model);

modelN = ‘halfBridgeTest’;
in = Simulink.SimulationInput(modelN);

parpool(‘LocalProfile1’)
tic; out = parsim(in, ‘UseFastRestart’,’on’); toc

delete(gcp(‘nocreate’)); I made a simulink spice model for a circuit and it is taking around 30 minutes to compile, I thought it was normal, but checking windows task manager it seems that only one thread of my cpu is at it’s maximum capacity, i tried using different configurations of workers and threads per worker, but nothing work it is still using arount 21% of the total of my CPU.
My simulink model has only one .slx
I am using this code for the parallel computing part
bdclose all;
%proj = openProject(‘.C:UsersfernaDownloadshalfBridgeTest.slx’);
model = ‘DownloadshalfBridgeTest.slx’;
open_system(model);

modelN = ‘halfBridgeTest’;
in = Simulink.SimulationInput(modelN);

parpool(‘LocalProfile1’)
tic; out = parsim(in, ‘UseFastRestart’,’on’); toc

delete(gcp(‘nocreate’)); parallel computing, parallel computing toolbox, simulink MATLAB Answers — New Questions

​

Folks,
In the world of artificial intelligence and more intelligent programming, I would like to see more intelligence put into place with how function like griddata, imagesc, pcolor, and surf interpret their inputs. There is an unfortunate degree of confusion that has persisted since the early 2000’s at least with how to interpret arrays in terms of Cartesian axes. I am troubled today with trying to understand how griddata is working on input that I setup using ndgrid. I appear to have something wrong, and earth layers are not dipping in the direction that I expect. The documentation says griddata can work with either meshgrid or griddata input, which makes my head spin given my understanding of both meshgrid and ndgrid. What is really troubling is that the Mathworks documentation routinely contains only simple examples where the person that created the documentation made "quicky" non-realistic examples where they simply created input arrays that had exactly the same x and y dimensions, which does not help anyone in my situation who is dealing with realistic inputs that do not have the same dimension lengths. I request that future documentation efforts spend a little extra time making non-symmetric input x and y arrays as examples.Folks,
In the world of artificial intelligence and more intelligent programming, I would like to see more intelligence put into place with how function like griddata, imagesc, pcolor, and surf interpret their inputs. There is an unfortunate degree of confusion that has persisted since the early 2000’s at least with how to interpret arrays in terms of Cartesian axes. I am troubled today with trying to understand how griddata is working on input that I setup using ndgrid. I appear to have something wrong, and earth layers are not dipping in the direction that I expect. The documentation says griddata can work with either meshgrid or griddata input, which makes my head spin given my understanding of both meshgrid and ndgrid. What is really troubling is that the Mathworks documentation routinely contains only simple examples where the person that created the documentation made "quicky" non-realistic examples where they simply created input arrays that had exactly the same x and y dimensions, which does not help anyone in my situation who is dealing with realistic inputs that do not have the same dimension lengths. I request that future documentation efforts spend a little extra time making non-symmetric input x and y arrays as examples. Folks,
In the world of artificial intelligence and more intelligent programming, I would like to see more intelligence put into place with how function like griddata, imagesc, pcolor, and surf interpret their inputs. There is an unfortunate degree of confusion that has persisted since the early 2000’s at least with how to interpret arrays in terms of Cartesian axes. I am troubled today with trying to understand how griddata is working on input that I setup using ndgrid. I appear to have something wrong, and earth layers are not dipping in the direction that I expect. The documentation says griddata can work with either meshgrid or griddata input, which makes my head spin given my understanding of both meshgrid and ndgrid. What is really troubling is that the Mathworks documentation routinely contains only simple examples where the person that created the documentation made "quicky" non-realistic examples where they simply created input arrays that had exactly the same x and y dimensions, which does not help anyone in my situation who is dealing with realistic inputs that do not have the same dimension lengths. I request that future documentation efforts spend a little extra time making non-symmetric input x and y arrays as examples. meshgrid, ndgrid, imagesc, pcolor, surf, griddata, slice, obliqueslice MATLAB Answers — New Questions

​

Hi,
I am running a fresh install of MATLAB R2022b on Ubuntu 22.04.
Laptop: HP Zbook Fury G7 (screen resolution 3840×2160)
GPU1: Intel Cometlake-H GT2
GPU2: NVidia Quadro T1000.
MATLAB install script was executed as sudo, as described here (link [MATLAB]). There have been several related questions in MATLAB Answers (link1, link2, and many more related to Windows) but none seem to work for this case.
Few observations:
If xrandr is not used, the scaling setting is completely ignored.
Executing the xrandr with the calculated DPI, seems to affect only the splash screen, but not the MATLAB interface.
After xrandr, changing the scaling setting in MATLAB affects the editor only (without restart). This is behavior is again lost after restart.
Changing permission (as suggested by one comment) in the ~/.matlab file, did not work.
Installing MATLAB as non-sudo yields the same results.
Anyone knows if there is anything else I could try? Besides lowering the screen resolution, since that results in blurriness.
Thanks!

Edit 1: Typo
Edit 2: Looking around it seems to be a permission issue. For testing purposes only, I added ‘root’ user to the license and when changing the scaling setting it is honored as expected. In the ~/.matlab folder for the root user, the main differences is the presense of *.mlsettings binary files. Although, giving full persmissions to the $USER for both ~/.matlab as well as /usr/local/MATLAB folder does not seem to affect the process in any way.
Current workaround: copying matlab.mlsettings file from the root to the user’s .matlab directory seems fix the issue. But this is far from a solution. Modyfing any setting of these settings/preferences require to first run matlab as root, make the modifitiations and then copy-paste the relevant *.mlsettings files. Will update when I have more.
Edit 3: A better workaround (no root needed): It seems that if a desktop launcher is used (matlab-support package), bash is not run in advance and MATLAB does not access the system enviroment variables, including the TMPDIR/TMP. Then (for some reason..) MATLAB can not access the /tmp/ folder and this is probably where things break. Two ways go around this are:
Run matlab from terminal where bashrc is already sourced (including for example a TMP var to an accessible folder, e.g. ~/.tmp/).
Or, change the default MATLAB tempdir. This is inspired from the workaround of ‘Invalid cross-device link (18)’ error I also exprerienced when trying to save a document (link3). Although, this setting is again lost after a restart, at least for me.Hi,
I am running a fresh install of MATLAB R2022b on Ubuntu 22.04.
Laptop: HP Zbook Fury G7 (screen resolution 3840×2160)
GPU1: Intel Cometlake-H GT2
GPU2: NVidia Quadro T1000.
MATLAB install script was executed as sudo, as described here (link [MATLAB]). There have been several related questions in MATLAB Answers (link1, link2, and many more related to Windows) but none seem to work for this case.
Few observations:
If xrandr is not used, the scaling setting is completely ignored.
Executing the xrandr with the calculated DPI, seems to affect only the splash screen, but not the MATLAB interface.
After xrandr, changing the scaling setting in MATLAB affects the editor only (without restart). This is behavior is again lost after restart.
Changing permission (as suggested by one comment) in the ~/.matlab file, did not work.
Installing MATLAB as non-sudo yields the same results.
Anyone knows if there is anything else I could try? Besides lowering the screen resolution, since that results in blurriness.
Thanks!

Edit 1: Typo
Edit 2: Looking around it seems to be a permission issue. For testing purposes only, I added ‘root’ user to the license and when changing the scaling setting it is honored as expected. In the ~/.matlab folder for the root user, the main differences is the presense of *.mlsettings binary files. Although, giving full persmissions to the $USER for both ~/.matlab as well as /usr/local/MATLAB folder does not seem to affect the process in any way.
Current workaround: copying matlab.mlsettings file from the root to the user’s .matlab directory seems fix the issue. But this is far from a solution. Modyfing any setting of these settings/preferences require to first run matlab as root, make the modifitiations and then copy-paste the relevant *.mlsettings files. Will update when I have more.
Edit 3: A better workaround (no root needed): It seems that if a desktop launcher is used (matlab-support package), bash is not run in advance and MATLAB does not access the system enviroment variables, including the TMPDIR/TMP. Then (for some reason..) MATLAB can not access the /tmp/ folder and this is probably where things break. Two ways go around this are:
Run matlab from terminal where bashrc is already sourced (including for example a TMP var to an accessible folder, e.g. ~/.tmp/).
Or, change the default MATLAB tempdir. This is inspired from the workaround of ‘Invalid cross-device link (18)’ error I also exprerienced when trying to save a document (link3). Although, this setting is again lost after a restart, at least for me. Hi,
I am running a fresh install of MATLAB R2022b on Ubuntu 22.04.
Laptop: HP Zbook Fury G7 (screen resolution 3840×2160)
GPU1: Intel Cometlake-H GT2
GPU2: NVidia Quadro T1000.
MATLAB install script was executed as sudo, as described here (link [MATLAB]). There have been several related questions in MATLAB Answers (link1, link2, and many more related to Windows) but none seem to work for this case.
Few observations:
If xrandr is not used, the scaling setting is completely ignored.
Executing the xrandr with the calculated DPI, seems to affect only the splash screen, but not the MATLAB interface.
After xrandr, changing the scaling setting in MATLAB affects the editor only (without restart). This is behavior is again lost after restart.
Changing permission (as suggested by one comment) in the ~/.matlab file, did not work.
Installing MATLAB as non-sudo yields the same results.
Anyone knows if there is anything else I could try? Besides lowering the screen resolution, since that results in blurriness.
Thanks!

Edit 1: Typo
Edit 2: Looking around it seems to be a permission issue. For testing purposes only, I added ‘root’ user to the license and when changing the scaling setting it is honored as expected. In the ~/.matlab folder for the root user, the main differences is the presense of *.mlsettings binary files. Although, giving full persmissions to the $USER for both ~/.matlab as well as /usr/local/MATLAB folder does not seem to affect the process in any way.
Current workaround: copying matlab.mlsettings file from the root to the user’s .matlab directory seems fix the issue. But this is far from a solution. Modyfing any setting of these settings/preferences require to first run matlab as root, make the modifitiations and then copy-paste the relevant *.mlsettings files. Will update when I have more.
Edit 3: A better workaround (no root needed): It seems that if a desktop launcher is used (matlab-support package), bash is not run in advance and MATLAB does not access the system enviroment variables, including the TMPDIR/TMP. Then (for some reason..) MATLAB can not access the /tmp/ folder and this is probably where things break. Two ways go around this are:
Run matlab from terminal where bashrc is already sourced (including for example a TMP var to an accessible folder, e.g. ~/.tmp/).
Or, change the default MATLAB tempdir. This is inspired from the workaround of ‘Invalid cross-device link (18)’ error I also exprerienced when trying to save a document (link3). Although, this setting is again lost after a restart, at least for me. hidpi, linux, ubuntu MATLAB Answers — New Questions

​

I have a cell array of millions of strings representing dates with the format "yyyyMMddHHmmss"
I need to convert these to datetimes. After many attempts of various kinds I think I have found an optimal solution.
However, my solution requires that I use str2num instead of str2double and results in nearly 100x increase in speed. This is depite the fact that MATLAB recommends using str2double for "faster performance" and specifically discourages str2num.
In particular, str2double cannot convert a char array and results in Inf, while str2num converts the char array without issue.
Below is an example script.

(P.S. not directly related to this question, but if there is a faster way to convert cell arrays of strings to datetimes, let me know!)

%Make example input data
t1 = datetime(2000,1,1,0,0,0);
t2 = datetime("now");
t = string(datestr(t1:days(1):t2,’yyyymmddHHMMss’));

t_cell = cellstr(t); %<— This is the "cell array" example data

%Option 1: datetime cell array of strings
% —> Very slow (~0.75 s)
tic
tcheck1 = datetime(t_cell,’InputFormat’,’yyyyMMddHHmmss’);
toc

%Option 2: str2double
% —> DOES NOT WORK (results in Inf)
tic
da = char(t_cell);
year1 = str2double(da(:,1:4));
month1 = str2double(da(:,5:6));
day1 = str2double(da(:,7:8));
hour1 = str2double(da(:,9:10));
min1 = str2double(da(:,11:12));
sec1 = str2double(da(:,13:14));
tcheck2 = datetime(year1,month1,day1,hour1,min1,sec1);
toc

%Option 3: str2double with extra conversion from char to string
% —> About twice as fast as Option #1 (~0.4 s)
tic
da = char(t_cell);
year1 = str2double(string(da(:,1:4)));
month1 = str2double(string(da(:,5:6)));
day1 = str2double(string(da(:,7:8)));
hour1 = str2double(string(da(:,9:10)));
min1 = str2double(string(da(:,11:12)));
sec1 = str2double(string(da(:,13:14)));
tcheck3 = datetime(year1,month1,day1,hour1,min1,sec1);
toc

%Option 3: str2num
% —> About 100 times faster than Option #1 and #3 (~0.005 s)
tic
da = char(t_cell);
year1 = str2num(da(:,1:4));
month1 = str2num(da(:,5:6));
day1 = str2num(da(:,7:8));
hour1 = str2num(da(:,9:10));
min1 = str2num(da(:,11:12));
sec1 = str2num(da(:,13:14));
tcheck4 = datetime(year1,month1,day1,hour1,min1,sec1);
tocI have a cell array of millions of strings representing dates with the format "yyyyMMddHHmmss"
I need to convert these to datetimes. After many attempts of various kinds I think I have found an optimal solution.
However, my solution requires that I use str2num instead of str2double and results in nearly 100x increase in speed. This is depite the fact that MATLAB recommends using str2double for "faster performance" and specifically discourages str2num.
In particular, str2double cannot convert a char array and results in Inf, while str2num converts the char array without issue.
Below is an example script.

(P.S. not directly related to this question, but if there is a faster way to convert cell arrays of strings to datetimes, let me know!)

%Make example input data
t1 = datetime(2000,1,1,0,0,0);
t2 = datetime("now");
t = string(datestr(t1:days(1):t2,’yyyymmddHHMMss’));

t_cell = cellstr(t); %<— This is the "cell array" example data

%Option 1: datetime cell array of strings
% —> Very slow (~0.75 s)
tic
tcheck1 = datetime(t_cell,’InputFormat’,’yyyyMMddHHmmss’);
toc

%Option 2: str2double
% —> DOES NOT WORK (results in Inf)
tic
da = char(t_cell);
year1 = str2double(da(:,1:4));
month1 = str2double(da(:,5:6));
day1 = str2double(da(:,7:8));
hour1 = str2double(da(:,9:10));
min1 = str2double(da(:,11:12));
sec1 = str2double(da(:,13:14));
tcheck2 = datetime(year1,month1,day1,hour1,min1,sec1);
toc

%Option 3: str2double with extra conversion from char to string
% —> About twice as fast as Option #1 (~0.4 s)
tic
da = char(t_cell);
year1 = str2double(string(da(:,1:4)));
month1 = str2double(string(da(:,5:6)));
day1 = str2double(string(da(:,7:8)));
hour1 = str2double(string(da(:,9:10)));
min1 = str2double(string(da(:,11:12)));
sec1 = str2double(string(da(:,13:14)));
tcheck3 = datetime(year1,month1,day1,hour1,min1,sec1);
toc

%Option 3: str2num
% —> About 100 times faster than Option #1 and #3 (~0.005 s)
tic
da = char(t_cell);
year1 = str2num(da(:,1:4));
month1 = str2num(da(:,5:6));
day1 = str2num(da(:,7:8));
hour1 = str2num(da(:,9:10));
min1 = str2num(da(:,11:12));
sec1 = str2num(da(:,13:14));
tcheck4 = datetime(year1,month1,day1,hour1,min1,sec1);
toc I have a cell array of millions of strings representing dates with the format "yyyyMMddHHmmss"
I need to convert these to datetimes. After many attempts of various kinds I think I have found an optimal solution.
However, my solution requires that I use str2num instead of str2double and results in nearly 100x increase in speed. This is depite the fact that MATLAB recommends using str2double for "faster performance" and specifically discourages str2num.
In particular, str2double cannot convert a char array and results in Inf, while str2num converts the char array without issue.
Below is an example script.

(P.S. not directly related to this question, but if there is a faster way to convert cell arrays of strings to datetimes, let me know!)

%Make example input data
t1 = datetime(2000,1,1,0,0,0);
t2 = datetime("now");
t = string(datestr(t1:days(1):t2,’yyyymmddHHMMss’));

t_cell = cellstr(t); %<— This is the "cell array" example data

%Option 1: datetime cell array of strings
% —> Very slow (~0.75 s)
tic
tcheck1 = datetime(t_cell,’InputFormat’,’yyyyMMddHHmmss’);
toc

%Option 2: str2double
% —> DOES NOT WORK (results in Inf)
tic
da = char(t_cell);
year1 = str2double(da(:,1:4));
month1 = str2double(da(:,5:6));
day1 = str2double(da(:,7:8));
hour1 = str2double(da(:,9:10));
min1 = str2double(da(:,11:12));
sec1 = str2double(da(:,13:14));
tcheck2 = datetime(year1,month1,day1,hour1,min1,sec1);
toc

%Option 3: str2double with extra conversion from char to string
% —> About twice as fast as Option #1 (~0.4 s)
tic
da = char(t_cell);
year1 = str2double(string(da(:,1:4)));
month1 = str2double(string(da(:,5:6)));
day1 = str2double(string(da(:,7:8)));
hour1 = str2double(string(da(:,9:10)));
min1 = str2double(string(da(:,11:12)));
sec1 = str2double(string(da(:,13:14)));
tcheck3 = datetime(year1,month1,day1,hour1,min1,sec1);
toc

%Option 3: str2num
% —> About 100 times faster than Option #1 and #3 (~0.005 s)
tic
da = char(t_cell);
year1 = str2num(da(:,1:4));
month1 = str2num(da(:,5:6));
day1 = str2num(da(:,7:8));
hour1 = str2num(da(:,9:10));
min1 = str2num(da(:,11:12));
sec1 = str2num(da(:,13:14));
tcheck4 = datetime(year1,month1,day1,hour1,min1,sec1);
toc datetime, string, double, convert MATLAB Answers — New Questions

​