When using spectrogram to calculate power spectral density for a large dataset, the plot produced by directly running the command with no output arguments is slightly different from what I get when I run it with an output argument and plot that output myself.

For example, the following plots spectrograms for a subset of my data and compares the direct result of spectrogram with the output raster:
load(‘exampledata.mat’)
window = 10000;
noverlap = round(0.1*window);
fs = 10000;

figure(1);clf
t = tiledlayout(3,1, ‘TileIndexing’, ‘columnmajor’);

% Plot spectrogram directly from spectrogram function
s(1) = nexttile;
spectrogram(exampledata,window,noverlap,window,fs);
title(‘Original spectrogram plot (real data)’)
PSDdB_orig = get(get(gca,’Children’),’CData’);
caxis([min(PSDdB_orig,[],’all’) max(PSDdB_orig,[],’all’)])

% Calculate power spectral density and plot as decibels
[~,F,T,PSD] = spectrogram(exampledata,window,noverlap,window,fs);
PSDdB = (10.*log10(PSD))’;

s(2) = nexttile;
imagesc(F./1000,T./60,PSDdB)
title(‘Spectrogram output raster (real data)’)
c = colorbar;
caxis([min(PSDdB,[],’all’) max(PSDdB,[],’all’)])
set(get(c,’label’),’string’,’Power/frequency (dB/Hz)’,’Rotation’,90);

% Calculate ratio of the two approaches above and plot that
PSDdiff = PSDdB_orig./PSDdB;

s(3) = nexttile;
imagesc(F./1000,T./60,PSDdiff)
title(‘Original plot data divided by output raster data’)
c = colorbar;
caxis([min(PSDdiff,[],’all’) max(PSDdiff,[],’all’)])
set(get(c,’label’),’string’,’original/output’,’Rotation’,90);
set(s(2:3),’YDir’,’normal’)
xlabel(s(2:3), s(1).XLabel.String)
ylabel(s(2:3), s(1).YLabel.String)

From the figures above, it looks like they produce nearly the same result, except at high frequencies (the middle figure looks more different than the first mostly due to the different color scales).
Comparing the ranges and plotting a cross-section (example spectra at a single time) from each one shows that the difference seems to be that spectrogram’s direct plotting method is cutting off local minima:
disp([‘min/max of original spectrogram plot: ‘,num2str(min(PSDdB_orig,[],’all’)),’, ‘,num2str(max(PSDdB_orig,[],’all’))])
disp([‘min/max of spectrogram output raster: ‘,num2str(min(PSDdB,[],’all’)),’, ‘,num2str(max(PSDdB,[],’all’))])
% Plot example spectra from each approach
figure(2);clf
subplot(2,1,1);
plot(F./1000,PSDdB(10,:),F./1000,PSDdB_orig(10,:),’–‘);
legend(‘Spectrogram output raster’,’Original spectrogram’)
title(‘Example spectra’)
xlabel(‘Frequency (kHz)’)
ylabel(‘Power/frequency (dB/Hz)’)

% zoom in on high frequency range where values differ
subplot(2,1,2,copyobj(gca,gcf))
xlim([4.75 4.85])
title(‘high frequency close-up’)

But weirdly, I can’t reproduce this with randomly generated synthetic data:
x = randn(length(exampledata),1);

figure(3);clf

t = tiledlayout(3,1, ‘TileIndexing’, ‘columnmajor’);

s(1) = nexttile;
spectrogram(x,window,noverlap,window,fs);
title(‘Original spectrogram plot (synthetic data)’)
PSDdB_orig = get(get(gca,’Children’),’CData’);
caxis([min(PSDdB_orig,[],’all’) max(PSDdB_orig,[],’all’)])

[~,F,T,PSD] = spectrogram(x,window,noverlap,window,fs);
PSDdB = (10.*log10(PSD))’;
PSDdiff = PSDdB_orig./PSDdB;

s(2) = nexttile;
imagesc(F./1000,T./60,PSDdB)
title(‘Spectrogram output raster (synthetic data)’)
c = colorbar;
caxis([min(PSDdB,[],’all’) max(PSDdB,[],’all’)])
set(get(c,’label’),’string’,’Power/frequency (dB/Hz)’,’Rotation’,90);

s(3) = nexttile;
imagesc(F./1000,T./60,PSDdiff)
title(‘Original plot data divided by output raster data’)
c = colorbar;
caxis([min(PSDdiff,[],’all’) max(PSDdiff,[],’all’)])
set(get(c,’label’),’string’,’original/output’,’Rotation’,90);

set(s(2:3),’YDir’,’normal’)
xlabel(s(2:3), s(1).XLabel.String)
ylabel(s(2:3), s(1).YLabel.String)
disp([‘min/max of original spectrogram plot: ‘,num2str(min(PSDdB_orig,[],’all’)),’, ‘,num2str(max(PSDdB_orig,[],’all’))])
disp([‘min/max of spectrogram output raster: ‘,num2str(min(PSDdB,[],’all’)),’, ‘,num2str(max(PSDdB,[],’all’))])

I do notice that the minimum PSD value for my data (-196 dB) is significantly lower than the minimum of the synthetic data. Is there a lower limit where spectrogram starts to censor spectra (say, around -156.5351 dB)? Or is something else going on here? Any help would be much appreciated!! Thanks!When using spectrogram to calculate power spectral density for a large dataset, the plot produced by directly running the command with no output arguments is slightly different from what I get when I run it with an output argument and plot that output myself.

For example, the following plots spectrograms for a subset of my data and compares the direct result of spectrogram with the output raster:
load(‘exampledata.mat’)
window = 10000;
noverlap = round(0.1*window);
fs = 10000;

figure(1);clf
t = tiledlayout(3,1, ‘TileIndexing’, ‘columnmajor’);

% Plot spectrogram directly from spectrogram function
s(1) = nexttile;
spectrogram(exampledata,window,noverlap,window,fs);
title(‘Original spectrogram plot (real data)’)
PSDdB_orig = get(get(gca,’Children’),’CData’);
caxis([min(PSDdB_orig,[],’all’) max(PSDdB_orig,[],’all’)])

% Calculate power spectral density and plot as decibels
[~,F,T,PSD] = spectrogram(exampledata,window,noverlap,window,fs);
PSDdB = (10.*log10(PSD))’;

s(2) = nexttile;
imagesc(F./1000,T./60,PSDdB)
title(‘Spectrogram output raster (real data)’)
c = colorbar;
caxis([min(PSDdB,[],’all’) max(PSDdB,[],’all’)])
set(get(c,’label’),’string’,’Power/frequency (dB/Hz)’,’Rotation’,90);

% Calculate ratio of the two approaches above and plot that
PSDdiff = PSDdB_orig./PSDdB;

s(3) = nexttile;
imagesc(F./1000,T./60,PSDdiff)
title(‘Original plot data divided by output raster data’)
c = colorbar;
caxis([min(PSDdiff,[],’all’) max(PSDdiff,[],’all’)])
set(get(c,’label’),’string’,’original/output’,’Rotation’,90);
set(s(2:3),’YDir’,’normal’)
xlabel(s(2:3), s(1).XLabel.String)
ylabel(s(2:3), s(1).YLabel.String)

From the figures above, it looks like they produce nearly the same result, except at high frequencies (the middle figure looks more different than the first mostly due to the different color scales).
Comparing the ranges and plotting a cross-section (example spectra at a single time) from each one shows that the difference seems to be that spectrogram’s direct plotting method is cutting off local minima:
disp([‘min/max of original spectrogram plot: ‘,num2str(min(PSDdB_orig,[],’all’)),’, ‘,num2str(max(PSDdB_orig,[],’all’))])
disp([‘min/max of spectrogram output raster: ‘,num2str(min(PSDdB,[],’all’)),’, ‘,num2str(max(PSDdB,[],’all’))])
% Plot example spectra from each approach
figure(2);clf
subplot(2,1,1);
plot(F./1000,PSDdB(10,:),F./1000,PSDdB_orig(10,:),’–‘);
legend(‘Spectrogram output raster’,’Original spectrogram’)
title(‘Example spectra’)
xlabel(‘Frequency (kHz)’)
ylabel(‘Power/frequency (dB/Hz)’)

% zoom in on high frequency range where values differ
subplot(2,1,2,copyobj(gca,gcf))
xlim([4.75 4.85])
title(‘high frequency close-up’)

But weirdly, I can’t reproduce this with randomly generated synthetic data:
x = randn(length(exampledata),1);

figure(3);clf

t = tiledlayout(3,1, ‘TileIndexing’, ‘columnmajor’);

s(1) = nexttile;
spectrogram(x,window,noverlap,window,fs);
title(‘Original spectrogram plot (synthetic data)’)
PSDdB_orig = get(get(gca,’Children’),’CData’);
caxis([min(PSDdB_orig,[],’all’) max(PSDdB_orig,[],’all’)])

[~,F,T,PSD] = spectrogram(x,window,noverlap,window,fs);
PSDdB = (10.*log10(PSD))’;
PSDdiff = PSDdB_orig./PSDdB;

s(2) = nexttile;
imagesc(F./1000,T./60,PSDdB)
title(‘Spectrogram output raster (synthetic data)’)
c = colorbar;
caxis([min(PSDdB,[],’all’) max(PSDdB,[],’all’)])
set(get(c,’label’),’string’,’Power/frequency (dB/Hz)’,’Rotation’,90);

s(3) = nexttile;
imagesc(F./1000,T./60,PSDdiff)
title(‘Original plot data divided by output raster data’)
c = colorbar;
caxis([min(PSDdiff,[],’all’) max(PSDdiff,[],’all’)])
set(get(c,’label’),’string’,’original/output’,’Rotation’,90);

set(s(2:3),’YDir’,’normal’)
xlabel(s(2:3), s(1).XLabel.String)
ylabel(s(2:3), s(1).YLabel.String)
disp([‘min/max of original spectrogram plot: ‘,num2str(min(PSDdB_orig,[],’all’)),’, ‘,num2str(max(PSDdB_orig,[],’all’))])
disp([‘min/max of spectrogram output raster: ‘,num2str(min(PSDdB,[],’all’)),’, ‘,num2str(max(PSDdB,[],’all’))])

I do notice that the minimum PSD value for my data (-196 dB) is significantly lower than the minimum of the synthetic data. Is there a lower limit where spectrogram starts to censor spectra (say, around -156.5351 dB)? Or is something else going on here? Any help would be much appreciated!! Thanks! When using spectrogram to calculate power spectral density for a large dataset, the plot produced by directly running the command with no output arguments is slightly different from what I get when I run it with an output argument and plot that output myself.

For example, the following plots spectrograms for a subset of my data and compares the direct result of spectrogram with the output raster:
load(‘exampledata.mat’)
window = 10000;
noverlap = round(0.1*window);
fs = 10000;

figure(1);clf
t = tiledlayout(3,1, ‘TileIndexing’, ‘columnmajor’);

% Plot spectrogram directly from spectrogram function
s(1) = nexttile;
spectrogram(exampledata,window,noverlap,window,fs);
title(‘Original spectrogram plot (real data)’)
PSDdB_orig = get(get(gca,’Children’),’CData’);
caxis([min(PSDdB_orig,[],’all’) max(PSDdB_orig,[],’all’)])

% Calculate power spectral density and plot as decibels
[~,F,T,PSD] = spectrogram(exampledata,window,noverlap,window,fs);
PSDdB = (10.*log10(PSD))’;

s(2) = nexttile;
imagesc(F./1000,T./60,PSDdB)
title(‘Spectrogram output raster (real data)’)
c = colorbar;
caxis([min(PSDdB,[],’all’) max(PSDdB,[],’all’)])
set(get(c,’label’),’string’,’Power/frequency (dB/Hz)’,’Rotation’,90);

% Calculate ratio of the two approaches above and plot that
PSDdiff = PSDdB_orig./PSDdB;

s(3) = nexttile;
imagesc(F./1000,T./60,PSDdiff)
title(‘Original plot data divided by output raster data’)
c = colorbar;
caxis([min(PSDdiff,[],’all’) max(PSDdiff,[],’all’)])
set(get(c,’label’),’string’,’original/output’,’Rotation’,90);
set(s(2:3),’YDir’,’normal’)
xlabel(s(2:3), s(1).XLabel.String)
ylabel(s(2:3), s(1).YLabel.String)

From the figures above, it looks like they produce nearly the same result, except at high frequencies (the middle figure looks more different than the first mostly due to the different color scales).
Comparing the ranges and plotting a cross-section (example spectra at a single time) from each one shows that the difference seems to be that spectrogram’s direct plotting method is cutting off local minima:
disp([‘min/max of original spectrogram plot: ‘,num2str(min(PSDdB_orig,[],’all’)),’, ‘,num2str(max(PSDdB_orig,[],’all’))])
disp([‘min/max of spectrogram output raster: ‘,num2str(min(PSDdB,[],’all’)),’, ‘,num2str(max(PSDdB,[],’all’))])
% Plot example spectra from each approach
figure(2);clf
subplot(2,1,1);
plot(F./1000,PSDdB(10,:),F./1000,PSDdB_orig(10,:),’–‘);
legend(‘Spectrogram output raster’,’Original spectrogram’)
title(‘Example spectra’)
xlabel(‘Frequency (kHz)’)
ylabel(‘Power/frequency (dB/Hz)’)

% zoom in on high frequency range where values differ
subplot(2,1,2,copyobj(gca,gcf))
xlim([4.75 4.85])
title(‘high frequency close-up’)

But weirdly, I can’t reproduce this with randomly generated synthetic data:
x = randn(length(exampledata),1);

figure(3);clf

t = tiledlayout(3,1, ‘TileIndexing’, ‘columnmajor’);

s(1) = nexttile;
spectrogram(x,window,noverlap,window,fs);
title(‘Original spectrogram plot (synthetic data)’)
PSDdB_orig = get(get(gca,’Children’),’CData’);
caxis([min(PSDdB_orig,[],’all’) max(PSDdB_orig,[],’all’)])

[~,F,T,PSD] = spectrogram(x,window,noverlap,window,fs);
PSDdB = (10.*log10(PSD))’;
PSDdiff = PSDdB_orig./PSDdB;

s(2) = nexttile;
imagesc(F./1000,T./60,PSDdB)
title(‘Spectrogram output raster (synthetic data)’)
c = colorbar;
caxis([min(PSDdB,[],’all’) max(PSDdB,[],’all’)])
set(get(c,’label’),’string’,’Power/frequency (dB/Hz)’,’Rotation’,90);

s(3) = nexttile;
imagesc(F./1000,T./60,PSDdiff)
title(‘Original plot data divided by output raster data’)
c = colorbar;
caxis([min(PSDdiff,[],’all’) max(PSDdiff,[],’all’)])
set(get(c,’label’),’string’,’original/output’,’Rotation’,90);

set(s(2:3),’YDir’,’normal’)
xlabel(s(2:3), s(1).XLabel.String)
ylabel(s(2:3), s(1).YLabel.String)
disp([‘min/max of original spectrogram plot: ‘,num2str(min(PSDdB_orig,[],’all’)),’, ‘,num2str(max(PSDdB_orig,[],’all’))])
disp([‘min/max of spectrogram output raster: ‘,num2str(min(PSDdB,[],’all’)),’, ‘,num2str(max(PSDdB,[],’all’))])

I do notice that the minimum PSD value for my data (-196 dB) is significantly lower than the minimum of the synthetic data. Is there a lower limit where spectrogram starts to censor spectra (say, around -156.5351 dB)? Or is something else going on here? Any help would be much appreciated!! Thanks! spectrogram, spectral analysis, signal processing MATLAB Answers — New Questions

​

hello community

please help me to understand why data does not show when I run a loop:
I have 2 files: @Data01.mat and @Data05.mat I want to extrac data points when conditions are met’
if I run my script with Data1 all the parameters are there:
figure;plot (Epm_nEngallc0_4, IKCtl_au16_0allc, ‘.’);

but if I run my script with Data1&2 the output is different and I get less data points

I would expect to have all data poins from @Data01.mat plus @Data05.mat
please help me to see what am I doing wrong.

clear all; %
clc; %

fprintf(‘select folder containing data filesn’);

currentpath=pwd; %%

datapath=uigetdir(”,’Select Data Folder’); %%

if (datapath == 0)
fprintf(‘Data directory was not selected…script will be terminatednn’);
return
end

prompt = ‘Do you want to export data as .xlsx?’;
save_data_excel = questdlg(prompt,’Save’,’Yes’,’No’,’Yes’);

cd(datapath); %%
files=dir(‘@*.mat’); %%
num_files=length(files(:,1)); %%

for i=1:num_files
fprintf(‘Progress: %d/%dnn’,i, num_files)
load(files(i,1).name)
idx = [false; diff(xzsen__ls_0_rs_) < 0];
idx1 = [false; diff(xzsen__ls_1_rs_) < 0];
idx2 = [false; diff(xzsen__ls_2_rs_) < 0];
idx3 = [false; diff(xzsen__ls_0_rs_) < 0];
idx4 = [false; diff(xzsen__ls_1_rs_) < 0];
idx5 = [false; diff(xzsen__ls_2_rs_) < 0];

for j=1:length(time)

if Epm_nEng(j) > 0 && IKCtl_DiagRefLvlMinErr_au16__ls_1_rs_(j) > 0.165 && IKCtl_DiagRefLvlMinErr_au16__ls_3_rs_(j) > 0.165
Epm_nEngallc1_3(j,1) = Epm_nEng(j);
end
if Epm_nEng(j) > 0 && IKCtl_DiagRefLvlMinErr_au16__ls_2_rs_(j) > 0.165 && IKCtl_DiagRefLvlMinErr_au16__ls_5_rs_(j) > 0.165
Epm_nEngallc2_5(j,1) = Epm_nEng(j);
end
if Epm_nEng(j) > 0 && IKCtl_DiagRefLvlMinErr_au16__ls_0_rs_(j) > 0.165 && IKCtl_DiagRefLvlMinErr_au16__ls_4_rs_(j) > 0.165
Epm_nEngallc0_4(j,1) = Epm_nEng(j);
end

if Epm_nEng(j) > 0 && IKCtl_DiagRefLvlMinErr_au16__ls_1_rs_(j) > 0.165 && IKCtl_DiagRefLvlMinErr_au16__ls_3_rs_(j) > 0.165
IKCtl_au16_1allc(j,1)= IKCtl_DiagRefLvlMinErr_au16__ls_1_rs_(j);
IKCtl_au16_3allc(j,1)= IKCtl_DiagRefLvlMinErr_au16__ls_3_rs_(j);
end
if Epm_nEng(j) > 0 && IKCtl_DiagRefLvlMinErr_au16__ls_2_rs_(j) > 0.165 && IKCtl_DiagRefLvlMinErr_au16__ls_5_rs_(j) > 0.165
IKCtl_au16_2allc(j,1)= IKCtl_DiagRefLvlMinErr_au16__ls_2_rs_(j);
IKCtl_au16_5allc(j,1)= IKCtl_DiagRefLvlMinErr_au16__ls_5_rs_(j);
end
if Epm_nEng(j) > 0 && IKCtl_DiagRefLvlMinErr_au16__ls_0_rs_(j) > 0.165 && IKCtl_DiagRefLvlMinErr_au16__ls_4_rs_(j) > 0.165
IKCtl_au16_0allc(j,1)= IKCtl_DiagRefLvlMinErr_au16__ls_0_rs_(j);
IKCtl_au16_4allc(j,1)= IKCtl_DiagRefLvlMinErr_au16__ls_4_rs_(j);
end

end

endhello community

please help me to understand why data does not show when I run a loop:
I have 2 files: @Data01.mat and @Data05.mat I want to extrac data points when conditions are met’
if I run my script with Data1 all the parameters are there:
figure;plot (Epm_nEngallc0_4, IKCtl_au16_0allc, ‘.’);

but if I run my script with Data1&2 the output is different and I get less data points

I would expect to have all data poins from @Data01.mat plus @Data05.mat
please help me to see what am I doing wrong.

clear all; %
clc; %

fprintf(‘select folder containing data filesn’);

currentpath=pwd; %%

datapath=uigetdir(”,’Select Data Folder’); %%

if (datapath == 0)
fprintf(‘Data directory was not selected…script will be terminatednn’);
return
end

prompt = ‘Do you want to export data as .xlsx?’;
save_data_excel = questdlg(prompt,’Save’,’Yes’,’No’,’Yes’);

cd(datapath); %%
files=dir(‘@*.mat’); %%
num_files=length(files(:,1)); %%

for i=1:num_files
fprintf(‘Progress: %d/%dnn’,i, num_files)
load(files(i,1).name)
idx = [false; diff(xzsen__ls_0_rs_) < 0];
idx1 = [false; diff(xzsen__ls_1_rs_) < 0];
idx2 = [false; diff(xzsen__ls_2_rs_) < 0];
idx3 = [false; diff(xzsen__ls_0_rs_) < 0];
idx4 = [false; diff(xzsen__ls_1_rs_) < 0];
idx5 = [false; diff(xzsen__ls_2_rs_) < 0];

for j=1:length(time)

if Epm_nEng(j) > 0 && IKCtl_DiagRefLvlMinErr_au16__ls_1_rs_(j) > 0.165 && IKCtl_DiagRefLvlMinErr_au16__ls_3_rs_(j) > 0.165
Epm_nEngallc1_3(j,1) = Epm_nEng(j);
end
if Epm_nEng(j) > 0 && IKCtl_DiagRefLvlMinErr_au16__ls_2_rs_(j) > 0.165 && IKCtl_DiagRefLvlMinErr_au16__ls_5_rs_(j) > 0.165
Epm_nEngallc2_5(j,1) = Epm_nEng(j);
end
if Epm_nEng(j) > 0 && IKCtl_DiagRefLvlMinErr_au16__ls_0_rs_(j) > 0.165 && IKCtl_DiagRefLvlMinErr_au16__ls_4_rs_(j) > 0.165
Epm_nEngallc0_4(j,1) = Epm_nEng(j);
end

if Epm_nEng(j) > 0 && IKCtl_DiagRefLvlMinErr_au16__ls_1_rs_(j) > 0.165 && IKCtl_DiagRefLvlMinErr_au16__ls_3_rs_(j) > 0.165
IKCtl_au16_1allc(j,1)= IKCtl_DiagRefLvlMinErr_au16__ls_1_rs_(j);
IKCtl_au16_3allc(j,1)= IKCtl_DiagRefLvlMinErr_au16__ls_3_rs_(j);
end
if Epm_nEng(j) > 0 && IKCtl_DiagRefLvlMinErr_au16__ls_2_rs_(j) > 0.165 && IKCtl_DiagRefLvlMinErr_au16__ls_5_rs_(j) > 0.165
IKCtl_au16_2allc(j,1)= IKCtl_DiagRefLvlMinErr_au16__ls_2_rs_(j);
IKCtl_au16_5allc(j,1)= IKCtl_DiagRefLvlMinErr_au16__ls_5_rs_(j);
end
if Epm_nEng(j) > 0 && IKCtl_DiagRefLvlMinErr_au16__ls_0_rs_(j) > 0.165 && IKCtl_DiagRefLvlMinErr_au16__ls_4_rs_(j) > 0.165
IKCtl_au16_0allc(j,1)= IKCtl_DiagRefLvlMinErr_au16__ls_0_rs_(j);
IKCtl_au16_4allc(j,1)= IKCtl_DiagRefLvlMinErr_au16__ls_4_rs_(j);
end

end

end hello community

please help me to understand why data does not show when I run a loop:
I have 2 files: @Data01.mat and @Data05.mat I want to extrac data points when conditions are met’
if I run my script with Data1 all the parameters are there:
figure;plot (Epm_nEngallc0_4, IKCtl_au16_0allc, ‘.’);

but if I run my script with Data1&2 the output is different and I get less data points

I would expect to have all data poins from @Data01.mat plus @Data05.mat
please help me to see what am I doing wrong.

clear all; %
clc; %

fprintf(‘select folder containing data filesn’);

currentpath=pwd; %%

datapath=uigetdir(”,’Select Data Folder’); %%

if (datapath == 0)
fprintf(‘Data directory was not selected…script will be terminatednn’);
return
end

prompt = ‘Do you want to export data as .xlsx?’;
save_data_excel = questdlg(prompt,’Save’,’Yes’,’No’,’Yes’);

cd(datapath); %%
files=dir(‘@*.mat’); %%
num_files=length(files(:,1)); %%

for i=1:num_files
fprintf(‘Progress: %d/%dnn’,i, num_files)
load(files(i,1).name)
idx = [false; diff(xzsen__ls_0_rs_) < 0];
idx1 = [false; diff(xzsen__ls_1_rs_) < 0];
idx2 = [false; diff(xzsen__ls_2_rs_) < 0];
idx3 = [false; diff(xzsen__ls_0_rs_) < 0];
idx4 = [false; diff(xzsen__ls_1_rs_) < 0];
idx5 = [false; diff(xzsen__ls_2_rs_) < 0];

for j=1:length(time)

if Epm_nEng(j) > 0 && IKCtl_DiagRefLvlMinErr_au16__ls_1_rs_(j) > 0.165 && IKCtl_DiagRefLvlMinErr_au16__ls_3_rs_(j) > 0.165
Epm_nEngallc1_3(j,1) = Epm_nEng(j);
end
if Epm_nEng(j) > 0 && IKCtl_DiagRefLvlMinErr_au16__ls_2_rs_(j) > 0.165 && IKCtl_DiagRefLvlMinErr_au16__ls_5_rs_(j) > 0.165
Epm_nEngallc2_5(j,1) = Epm_nEng(j);
end
if Epm_nEng(j) > 0 && IKCtl_DiagRefLvlMinErr_au16__ls_0_rs_(j) > 0.165 && IKCtl_DiagRefLvlMinErr_au16__ls_4_rs_(j) > 0.165
Epm_nEngallc0_4(j,1) = Epm_nEng(j);
end

if Epm_nEng(j) > 0 && IKCtl_DiagRefLvlMinErr_au16__ls_1_rs_(j) > 0.165 && IKCtl_DiagRefLvlMinErr_au16__ls_3_rs_(j) > 0.165
IKCtl_au16_1allc(j,1)= IKCtl_DiagRefLvlMinErr_au16__ls_1_rs_(j);
IKCtl_au16_3allc(j,1)= IKCtl_DiagRefLvlMinErr_au16__ls_3_rs_(j);
end
if Epm_nEng(j) > 0 && IKCtl_DiagRefLvlMinErr_au16__ls_2_rs_(j) > 0.165 && IKCtl_DiagRefLvlMinErr_au16__ls_5_rs_(j) > 0.165
IKCtl_au16_2allc(j,1)= IKCtl_DiagRefLvlMinErr_au16__ls_2_rs_(j);
IKCtl_au16_5allc(j,1)= IKCtl_DiagRefLvlMinErr_au16__ls_5_rs_(j);
end
if Epm_nEng(j) > 0 && IKCtl_DiagRefLvlMinErr_au16__ls_0_rs_(j) > 0.165 && IKCtl_DiagRefLvlMinErr_au16__ls_4_rs_(j) > 0.165
IKCtl_au16_0allc(j,1)= IKCtl_DiagRefLvlMinErr_au16__ls_0_rs_(j);
IKCtl_au16_4allc(j,1)= IKCtl_DiagRefLvlMinErr_au16__ls_4_rs_(j);
end

end

end loops, matlab MATLAB Answers — New Questions

​

I’m having difficulty getting a function to plot correctly in Matlab. The function is:
f(x) = x^3 – sin(x) – e^x
I’ve tried using the below but the graph is not how it should appear:
X = -4:0.01:10;
Y = X.^3 – (sin(X)) – (exp(X));
plot(X,Y)I’m having difficulty getting a function to plot correctly in Matlab. The function is:
f(x) = x^3 – sin(x) – e^x
I’ve tried using the below but the graph is not how it should appear:
X = -4:0.01:10;
Y = X.^3 – (sin(X)) – (exp(X));
plot(X,Y) I’m having difficulty getting a function to plot correctly in Matlab. The function is:
f(x) = x^3 – sin(x) – e^x
I’ve tried using the below but the graph is not how it should appear:
X = -4:0.01:10;
Y = X.^3 – (sin(X)) – (exp(X));
plot(X,Y) plot, function MATLAB Answers — New Questions

​

Hi all,
This might be a bit of a fruitless question but I just want to confirm there is no other method. I want to know if there is any way of vectorizing the following code:
array = [1,0,1,1,0,0,1];
for i = 2:length(array)-1
if array(i-1) ~= array(i+1)
% Generate a random bit (0 or 1)
random_bit = randi([0, 1]);
% Update the array in place
array(i) = mod(array(i) + random_bit, 2);
end
end
The array can be of any length as long as it is only fillled with 0s and 1s. The key part of the code is that I want to update the array by doing nearest neighbor checks and in such a way that the number of walls (array(i) ~= array(i+1) for i from 1 to size(array)) is constant. And it is this constrained logic of my code that leads me to believe I cannot do away with using for-loops.
The reason I wish to vectorize the code is because I will be doing monte-carlo sampling where I have a large number of these arrays and wish to update them all at the same time using the above update rule, so in the ideal scenario I wouldn’t have to use a nested for-loop to cycle through each sample.Hi all,
This might be a bit of a fruitless question but I just want to confirm there is no other method. I want to know if there is any way of vectorizing the following code:
array = [1,0,1,1,0,0,1];
for i = 2:length(array)-1
if array(i-1) ~= array(i+1)
% Generate a random bit (0 or 1)
random_bit = randi([0, 1]);
% Update the array in place
array(i) = mod(array(i) + random_bit, 2);
end
end
The array can be of any length as long as it is only fillled with 0s and 1s. The key part of the code is that I want to update the array by doing nearest neighbor checks and in such a way that the number of walls (array(i) ~= array(i+1) for i from 1 to size(array)) is constant. And it is this constrained logic of my code that leads me to believe I cannot do away with using for-loops.
The reason I wish to vectorize the code is because I will be doing monte-carlo sampling where I have a large number of these arrays and wish to update them all at the same time using the above update rule, so in the ideal scenario I wouldn’t have to use a nested for-loop to cycle through each sample. Hi all,
This might be a bit of a fruitless question but I just want to confirm there is no other method. I want to know if there is any way of vectorizing the following code:
array = [1,0,1,1,0,0,1];
for i = 2:length(array)-1
if array(i-1) ~= array(i+1)
% Generate a random bit (0 or 1)
random_bit = randi([0, 1]);
% Update the array in place
array(i) = mod(array(i) + random_bit, 2);
end
end
The array can be of any length as long as it is only fillled with 0s and 1s. The key part of the code is that I want to update the array by doing nearest neighbor checks and in such a way that the number of walls (array(i) ~= array(i+1) for i from 1 to size(array)) is constant. And it is this constrained logic of my code that leads me to believe I cannot do away with using for-loops.
The reason I wish to vectorize the code is because I will be doing monte-carlo sampling where I have a large number of these arrays and wish to update them all at the same time using the above update rule, so in the ideal scenario I wouldn’t have to use a nested for-loop to cycle through each sample. vectorization MATLAB Answers — New Questions

​

I’m trying to open my MATLAB file but it’s doesn’t open. keep on writting this error which I don’t understand because I lasp open my file on the 23/08/24.I’m trying to open my MATLAB file but it’s doesn’t open. keep on writting this error which I don’t understand because I lasp open my file on the 23/08/24. I’m trying to open my MATLAB file but it’s doesn’t open. keep on writting this error which I don’t understand because I lasp open my file on the 23/08/24. error dialog MATLAB Answers — New Questions

​

Is the following code allowed:
result = zeros(100,1);
parfor ii = 1:100

% do something
result(ii) = myfun(resultfromdoingsomething)

end

function result = myfun(inp)
% do something and write a file based on inp
status = system(command); % command executes an executable that reads in the file that was written and produces an output file
result = % read in the file produced by the executable and grab a value to return
% delete the files
end
Even if allowed, are there any risks to be concerned about?
Would also like to know if there are any differences between 2024a and 2019b in this regard.Is the following code allowed:
result = zeros(100,1);
parfor ii = 1:100

% do something
result(ii) = myfun(resultfromdoingsomething)

end

function result = myfun(inp)
% do something and write a file based on inp
status = system(command); % command executes an executable that reads in the file that was written and produces an output file
result = % read in the file produced by the executable and grab a value to return
% delete the files
end
Even if allowed, are there any risks to be concerned about?
Would also like to know if there are any differences between 2024a and 2019b in this regard. Is the following code allowed:
result = zeros(100,1);
parfor ii = 1:100

% do something
result(ii) = myfun(resultfromdoingsomething)

end

function result = myfun(inp)
% do something and write a file based on inp
status = system(command); % command executes an executable that reads in the file that was written and produces an output file
result = % read in the file produced by the executable and grab a value to return
% delete the files
end
Even if allowed, are there any risks to be concerned about?
Would also like to know if there are any differences between 2024a and 2019b in this regard. parfor, system command MATLAB Answers — New Questions

​

What are my license details?What are my license details? What are my license details?  MATLAB Answers — New Questions

​

I am initializing an empty structure array using empty brackets:

&gt;&gt; myStruct(3).myField = [];
Then, all the initialized structure arrays are of type "double":

&gt;&gt; {class(myStruct(1).myField), class(myStruct(2).myField), class(myStruct(3).myField)}

ans =

1×3 cell array

{‘double’} {‘double’} {‘double’}
Why do I get an unhelpful error of "Conversion to double from struct is not possible" only when appending a "struct" to the end of the last array entry?

For example, the following code snippet executes without an error, which changes the class of the first and second entries of "myStruct" to "struct":

&gt;&gt; myStruct(1).myField(2) = struct(‘myVar’, 3);
&gt;&gt; myStruct(2).myField(2) = struct(‘myVar’, 3);
&gt;&gt; {class(myStruct(1).myField), class(myStruct(2).myField), class(myStruct(3).myField)}

ans =

1×3 cell array

{‘struct’} {‘struct’} {‘double’}
However, executing a similar line of code for the last entry of "myStruct" does throw an error:

&gt;&gt; myStruct(3).myField(2) = struct(‘myVar’, 3);

Conversion to double from struct is not possible.I am initializing an empty structure array using empty brackets:

&gt;&gt; myStruct(3).myField = [];
Then, all the initialized structure arrays are of type "double":

&gt;&gt; {class(myStruct(1).myField), class(myStruct(2).myField), class(myStruct(3).myField)}

ans =

1×3 cell array

{‘double’} {‘double’} {‘double’}
Why do I get an unhelpful error of "Conversion to double from struct is not possible" only when appending a "struct" to the end of the last array entry?

For example, the following code snippet executes without an error, which changes the class of the first and second entries of "myStruct" to "struct":

&gt;&gt; myStruct(1).myField(2) = struct(‘myVar’, 3);
&gt;&gt; myStruct(2).myField(2) = struct(‘myVar’, 3);
&gt;&gt; {class(myStruct(1).myField), class(myStruct(2).myField), class(myStruct(3).myField)}

ans =

1×3 cell array

{‘struct’} {‘struct’} {‘double’}
However, executing a similar line of code for the last entry of "myStruct" does throw an error:

&gt;&gt; myStruct(3).myField(2) = struct(‘myVar’, 3);

Conversion to double from struct is not possible. I am initializing an empty structure array using empty brackets:

&gt;&gt; myStruct(3).myField = [];
Then, all the initialized structure arrays are of type "double":

&gt;&gt; {class(myStruct(1).myField), class(myStruct(2).myField), class(myStruct(3).myField)}

ans =

1×3 cell array

{‘double’} {‘double’} {‘double’}
Why do I get an unhelpful error of "Conversion to double from struct is not possible" only when appending a "struct" to the end of the last array entry?

For example, the following code snippet executes without an error, which changes the class of the first and second entries of "myStruct" to "struct":

&gt;&gt; myStruct(1).myField(2) = struct(‘myVar’, 3);
&gt;&gt; myStruct(2).myField(2) = struct(‘myVar’, 3);
&gt;&gt; {class(myStruct(1).myField), class(myStruct(2).myField), class(myStruct(3).myField)}

ans =

1×3 cell array

{‘struct’} {‘struct’} {‘double’}
However, executing a similar line of code for the last entry of "myStruct" does throw an error:

&gt;&gt; myStruct(3).myField(2) = struct(‘myVar’, 3);

Conversion to double from struct is not possible. structinitialization MATLAB Answers — New Questions

​

I am attempting to create a table that will display the results gotten from running through another MATLAB code however I just cannot seem to replace the values in the table with the new values.
I have the Table labeled so that I can output it but I don’t understand why I can’t replace the Table values (that I have currently stored as 0’s) with the outputs. I got and error originally saying that the right hand side needed to be a table or an array (Originally i just had the "minPModel" and such but since replaced them with the new table "MinMaxTab" and it still won’t accept it). I don’t understand how to get it to work.
Attached is the MinMax file
Table1 = table([0.50; 0.75; 1; 1.25; 1.5; 1.75; 2],…
[0; 0; 0; 0; 0; 0; 0],…
[0; 0; 0; 0; 0; 0; 0],…
[0; 0; 0; 0; 0; 0; 0],…
[0; 0; 0; 0; 0; 0; 0],…
‘VariableNames’,{‘R (mmHg*s/ml)’ ‘Pressure Maximum (mmHg)’ ‘Pressure Minimum (mmHg)’ ‘Presure Mean (mmHg)’ ‘Pulse Pressure (max-min) (mmHg)’});
for R = 0.5:.25:2
k = 2;
fprintf("R = %d", R);
run MinMax.m;
MinMaxTab = [minPModel; maxPModel; meanPModel];
Table1(2,k) = MinMaxTab(1,1);
Table1(3,k) = MinMaxTab(1,2);
Table1(4,k) = MinMaxTab(1,3);
Table1(5,k) = Table1(3,k)-Table1(2,k);

k=k+1;
end
Table1I am attempting to create a table that will display the results gotten from running through another MATLAB code however I just cannot seem to replace the values in the table with the new values.
I have the Table labeled so that I can output it but I don’t understand why I can’t replace the Table values (that I have currently stored as 0’s) with the outputs. I got and error originally saying that the right hand side needed to be a table or an array (Originally i just had the "minPModel" and such but since replaced them with the new table "MinMaxTab" and it still won’t accept it). I don’t understand how to get it to work.
Attached is the MinMax file
Table1 = table([0.50; 0.75; 1; 1.25; 1.5; 1.75; 2],…
[0; 0; 0; 0; 0; 0; 0],…
[0; 0; 0; 0; 0; 0; 0],…
[0; 0; 0; 0; 0; 0; 0],…
[0; 0; 0; 0; 0; 0; 0],…
‘VariableNames’,{‘R (mmHg*s/ml)’ ‘Pressure Maximum (mmHg)’ ‘Pressure Minimum (mmHg)’ ‘Presure Mean (mmHg)’ ‘Pulse Pressure (max-min) (mmHg)’});
for R = 0.5:.25:2
k = 2;
fprintf("R = %d", R);
run MinMax.m;
MinMaxTab = [minPModel; maxPModel; meanPModel];
Table1(2,k) = MinMaxTab(1,1);
Table1(3,k) = MinMaxTab(1,2);
Table1(4,k) = MinMaxTab(1,3);
Table1(5,k) = Table1(3,k)-Table1(2,k);

k=k+1;
end
Table1 I am attempting to create a table that will display the results gotten from running through another MATLAB code however I just cannot seem to replace the values in the table with the new values.
I have the Table labeled so that I can output it but I don’t understand why I can’t replace the Table values (that I have currently stored as 0’s) with the outputs. I got and error originally saying that the right hand side needed to be a table or an array (Originally i just had the "minPModel" and such but since replaced them with the new table "MinMaxTab" and it still won’t accept it). I don’t understand how to get it to work.
Attached is the MinMax file
Table1 = table([0.50; 0.75; 1; 1.25; 1.5; 1.75; 2],…
[0; 0; 0; 0; 0; 0; 0],…
[0; 0; 0; 0; 0; 0; 0],…
[0; 0; 0; 0; 0; 0; 0],…
[0; 0; 0; 0; 0; 0; 0],…
‘VariableNames’,{‘R (mmHg*s/ml)’ ‘Pressure Maximum (mmHg)’ ‘Pressure Minimum (mmHg)’ ‘Presure Mean (mmHg)’ ‘Pulse Pressure (max-min) (mmHg)’});
for R = 0.5:.25:2
k = 2;
fprintf("R = %d", R);
run MinMax.m;
MinMaxTab = [minPModel; maxPModel; meanPModel];
Table1(2,k) = MinMaxTab(1,1);
Table1(3,k) = MinMaxTab(1,2);
Table1(4,k) = MinMaxTab(1,3);
Table1(5,k) = Table1(3,k)-Table1(2,k);

k=k+1;
end
Table1 table, replacement, optimization MATLAB Answers — New Questions

​

Hi everyone,
I’ve been building a GUI based on a uifigure and the matlab.apps.AppBase tools. It’s not built in App Designer, I do it programmatically. I use a uigridlayout to position my various items; it works quite well for most things, but I’m having trouble with uiaxes.
These uiaxes are located within the uigridlayout, but I need to make a slight size adjustment after they’ve been created. I just need to adjust the width, I know by how many pixels to adjust it. If I run my app by typing "app = appName();" in the command window, the app shows up, the uiaxes are not adjusted. I then issue the command in the command window: "app.myAxes.Position(3) = app.myAxes.Position(3) – boxWidth;", which does exactly what I need it to do.
However, adding that line of code in the code that builds the actual GUI does not work, no matter where I try to put it. I’ve set AutoResizeChildren of the uifigure to off, no luck. I’ve searched here, but nothing I found seems to work.
So how do I get my app to execute that particular line of code?
Cheers,
ChristianeHi everyone,
I’ve been building a GUI based on a uifigure and the matlab.apps.AppBase tools. It’s not built in App Designer, I do it programmatically. I use a uigridlayout to position my various items; it works quite well for most things, but I’m having trouble with uiaxes.
These uiaxes are located within the uigridlayout, but I need to make a slight size adjustment after they’ve been created. I just need to adjust the width, I know by how many pixels to adjust it. If I run my app by typing "app = appName();" in the command window, the app shows up, the uiaxes are not adjusted. I then issue the command in the command window: "app.myAxes.Position(3) = app.myAxes.Position(3) – boxWidth;", which does exactly what I need it to do.
However, adding that line of code in the code that builds the actual GUI does not work, no matter where I try to put it. I’ve set AutoResizeChildren of the uifigure to off, no luck. I’ve searched here, but nothing I found seems to work.
So how do I get my app to execute that particular line of code?
Cheers,
Christiane Hi everyone,
I’ve been building a GUI based on a uifigure and the matlab.apps.AppBase tools. It’s not built in App Designer, I do it programmatically. I use a uigridlayout to position my various items; it works quite well for most things, but I’m having trouble with uiaxes.
These uiaxes are located within the uigridlayout, but I need to make a slight size adjustment after they’ve been created. I just need to adjust the width, I know by how many pixels to adjust it. If I run my app by typing "app = appName();" in the command window, the app shows up, the uiaxes are not adjusted. I then issue the command in the command window: "app.myAxes.Position(3) = app.myAxes.Position(3) – boxWidth;", which does exactly what I need it to do.
However, adding that line of code in the code that builds the actual GUI does not work, no matter where I try to put it. I’ve set AutoResizeChildren of the uifigure to off, no luck. I’ve searched here, but nothing I found seems to work.
So how do I get my app to execute that particular line of code?
Cheers,
Christiane uiaxes uigridlayout MATLAB Answers — New Questions

​