Hi there
I was customising the standard MATLAB Bode plot to make the gridlines, major and minor bold,
change the x and y label size and bold them and also customise the axis.
Then I tried to plot the straight line approximation, but I can only seem to access the phase plot, and not the magnitude plot.
For the two axes, ax(1) and ax(2), I have called them mag_ax and phase_ax.
I can access the other properties fine, but when I tries to add the lines, my code doesn’t recognise the mag_ax.
Any advice greatly appreciated

close all

s = tf(‘s’);

G_1 = tf(1/(0.1*s + 1));

figure(‘WindowState’,’maximized’);

gg = bodeplot(G_1);

title(‘Bode plot of $frac{1}{0.1s+1}$’,…
‘Interpreter’,’latex’,’FontSize’,18,’FontWeight’,’bold’);

gg.Responses.Color = "blue";
gg.Responses.LineWidth = 2;
gg.XLabel.FontWeight = "bold";

% Get the handles of the axes
ax = findobj(gcf,’type’,’axes’);
mag_ax = ax(1);
phase_ax = ax(2);

mag_ax.XLim = [0.1 1000];
mag_ax.YLim= [-60 +60];

phase_ax.XLim = [0.1 1000];
phase_ax.YLim= [-90 +90];

phase_ax.YTick = (-90:45:90);

grid on
grid minor
phase_ax.GridLineWidth = 1;
mag_ax.GridLineWidth = 1;

phase_ax.MinorGridLineStyle = ‘-‘;
mag_ax.MinorGridLineStyle = ‘-‘;

phase_ax.MinorGridLineWidth = 0.75;
mag_ax.MinorGridLineWidth = 0.75;

phase_ax.MinorGridAlpha = 0.5;
mag_ax.MinorGridAlpha = 0.5;

phase_ax.GridLineWidth = 1;
mag_ax.GridLineWidth = 1;

phase_ax.GridAlpha = 1;
mag_ax.GridAlpha = 1;

mag_ax.YLabel.FontWeight = "bold";
mag_ax.YLabel.FontSize = 12;

phase_ax.YLabel.FontWeight = "bold";
phase_ax.YLabel.FontSize = 12;

for k = 1:length(phase_ax)
xticks(phase_ax(k), [0.1 1 10 100 1000]); % Set desired tick positions
end
for k = 1:length(phase_ax)
phase_ax(k).XTickLabel = arrayfun(@(x) sprintf(‘%.1f’, x), phase_ax(k).XTick, ‘UniformOutput’, false);
end

set(phase_ax,’fontweight’,’bold’)
set(mag_ax,’fontweight’,’bold’)

gg.Responses.Visible = ‘on’;
gg.Responses.Color = ‘blue’;

mag_ax.NextPlot = ‘add’;
line([0.1 10.0],[0 0],’linewidth’,2,’color’,’red’);
line([10.0 1000],[0 -40],’linewidth’,2,’color’,’red’);

phase_ax.NextPlot = ‘add’;
line([0.1 1.0],[0 0],’linewidth’,2,’color’,’red’);
line([1.0 100],[0 -90],’linewidth’,2,’color’,’red’);
line([100 1000],[-90 -90],’linewidth’,2,’color’,’red’);Hi there
I was customising the standard MATLAB Bode plot to make the gridlines, major and minor bold,
change the x and y label size and bold them and also customise the axis.
Then I tried to plot the straight line approximation, but I can only seem to access the phase plot, and not the magnitude plot.
For the two axes, ax(1) and ax(2), I have called them mag_ax and phase_ax.
I can access the other properties fine, but when I tries to add the lines, my code doesn’t recognise the mag_ax.
Any advice greatly appreciated

close all

s = tf(‘s’);

G_1 = tf(1/(0.1*s + 1));

figure(‘WindowState’,’maximized’);

gg = bodeplot(G_1);

title(‘Bode plot of $frac{1}{0.1s+1}$’,…
‘Interpreter’,’latex’,’FontSize’,18,’FontWeight’,’bold’);

gg.Responses.Color = "blue";
gg.Responses.LineWidth = 2;
gg.XLabel.FontWeight = "bold";

% Get the handles of the axes
ax = findobj(gcf,’type’,’axes’);
mag_ax = ax(1);
phase_ax = ax(2);

mag_ax.XLim = [0.1 1000];
mag_ax.YLim= [-60 +60];

phase_ax.XLim = [0.1 1000];
phase_ax.YLim= [-90 +90];

phase_ax.YTick = (-90:45:90);

grid on
grid minor
phase_ax.GridLineWidth = 1;
mag_ax.GridLineWidth = 1;

phase_ax.MinorGridLineStyle = ‘-‘;
mag_ax.MinorGridLineStyle = ‘-‘;

phase_ax.MinorGridLineWidth = 0.75;
mag_ax.MinorGridLineWidth = 0.75;

phase_ax.MinorGridAlpha = 0.5;
mag_ax.MinorGridAlpha = 0.5;

phase_ax.GridLineWidth = 1;
mag_ax.GridLineWidth = 1;

phase_ax.GridAlpha = 1;
mag_ax.GridAlpha = 1;

mag_ax.YLabel.FontWeight = "bold";
mag_ax.YLabel.FontSize = 12;

phase_ax.YLabel.FontWeight = "bold";
phase_ax.YLabel.FontSize = 12;

for k = 1:length(phase_ax)
xticks(phase_ax(k), [0.1 1 10 100 1000]); % Set desired tick positions
end
for k = 1:length(phase_ax)
phase_ax(k).XTickLabel = arrayfun(@(x) sprintf(‘%.1f’, x), phase_ax(k).XTick, ‘UniformOutput’, false);
end

set(phase_ax,’fontweight’,’bold’)
set(mag_ax,’fontweight’,’bold’)

gg.Responses.Visible = ‘on’;
gg.Responses.Color = ‘blue’;

mag_ax.NextPlot = ‘add’;
line([0.1 10.0],[0 0],’linewidth’,2,’color’,’red’);
line([10.0 1000],[0 -40],’linewidth’,2,’color’,’red’);

phase_ax.NextPlot = ‘add’;
line([0.1 1.0],[0 0],’linewidth’,2,’color’,’red’);
line([1.0 100],[0 -90],’linewidth’,2,’color’,’red’);
line([100 1000],[-90 -90],’linewidth’,2,’color’,’red’); Hi there
I was customising the standard MATLAB Bode plot to make the gridlines, major and minor bold,
change the x and y label size and bold them and also customise the axis.
Then I tried to plot the straight line approximation, but I can only seem to access the phase plot, and not the magnitude plot.
For the two axes, ax(1) and ax(2), I have called them mag_ax and phase_ax.
I can access the other properties fine, but when I tries to add the lines, my code doesn’t recognise the mag_ax.
Any advice greatly appreciated

close all

s = tf(‘s’);

G_1 = tf(1/(0.1*s + 1));

figure(‘WindowState’,’maximized’);

gg = bodeplot(G_1);

title(‘Bode plot of $frac{1}{0.1s+1}$’,…
‘Interpreter’,’latex’,’FontSize’,18,’FontWeight’,’bold’);

gg.Responses.Color = "blue";
gg.Responses.LineWidth = 2;
gg.XLabel.FontWeight = "bold";

% Get the handles of the axes
ax = findobj(gcf,’type’,’axes’);
mag_ax = ax(1);
phase_ax = ax(2);

mag_ax.XLim = [0.1 1000];
mag_ax.YLim= [-60 +60];

phase_ax.XLim = [0.1 1000];
phase_ax.YLim= [-90 +90];

phase_ax.YTick = (-90:45:90);

grid on
grid minor
phase_ax.GridLineWidth = 1;
mag_ax.GridLineWidth = 1;

phase_ax.MinorGridLineStyle = ‘-‘;
mag_ax.MinorGridLineStyle = ‘-‘;

phase_ax.MinorGridLineWidth = 0.75;
mag_ax.MinorGridLineWidth = 0.75;

phase_ax.MinorGridAlpha = 0.5;
mag_ax.MinorGridAlpha = 0.5;

phase_ax.GridLineWidth = 1;
mag_ax.GridLineWidth = 1;

phase_ax.GridAlpha = 1;
mag_ax.GridAlpha = 1;

mag_ax.YLabel.FontWeight = "bold";
mag_ax.YLabel.FontSize = 12;

phase_ax.YLabel.FontWeight = "bold";
phase_ax.YLabel.FontSize = 12;

for k = 1:length(phase_ax)
xticks(phase_ax(k), [0.1 1 10 100 1000]); % Set desired tick positions
end
for k = 1:length(phase_ax)
phase_ax(k).XTickLabel = arrayfun(@(x) sprintf(‘%.1f’, x), phase_ax(k).XTick, ‘UniformOutput’, false);
end

set(phase_ax,’fontweight’,’bold’)
set(mag_ax,’fontweight’,’bold’)

gg.Responses.Visible = ‘on’;
gg.Responses.Color = ‘blue’;

mag_ax.NextPlot = ‘add’;
line([0.1 10.0],[0 0],’linewidth’,2,’color’,’red’);
line([10.0 1000],[0 -40],’linewidth’,2,’color’,’red’);

phase_ax.NextPlot = ‘add’;
line([0.1 1.0],[0 0],’linewidth’,2,’color’,’red’);
line([1.0 100],[0 -90],’linewidth’,2,’color’,’red’);
line([100 1000],[-90 -90],’linewidth’,2,’color’,’red’); bodeplot, matlab MATLAB Answers — New Questions

​

Dear all
I need help to add an algoritm or modified the exsit one to get the figures annexed in file:the following is my code:
clc; clear; close all;

%% —————- 1. Load Data ————————————
filename = ‘ThreeFaultModel_Modified.xlsx’;
data = xlsread(filename);

x = data(:,1);
g_Bouguer = data(:,2);
x = x(:); g_Bouguer = g_Bouguer(:);

%% —————- 2. User Inputs ———————————
N_layers = input(‘Enter number of layers: ‘);

rho_profiles = zeros(1, N_layers);
for i = 1:N_layers
rho_profiles(i) = input([‘Density of layer ‘ num2str(i) ‘: ‘]);
end

rho_basement = input(‘Basement density: ‘);
rho_contrasts = rho_profiles – rho_basement;

%% —————- 3. Inversion ————————
G = 6.67e-3;

z_inv = bsxfun(@rdivide, g_Bouguer, (2*pi*G*rho_contrasts));

%% —————- 4. Detect ONE Main Fault ————————
VG = gradient(z_inv(:,1), x);

% اختيار أقوى تغير (fault)
[~, idx_fault] = max(abs(VG));

MainFault.x = x(idx_fault);
MainFault.dip = atan2d(VG(idx_fault),1); % تقدير تقريبي
MainFault.throw = max(z_inv(:,1)) * 0.3; % تقدير بسيط
MainFault.type = ‘Normal’;

if MainFault.dip > 0
MainFault.type = ‘Reverse’;
end
if abs(MainFault.dip) > 85
MainFault.type = ‘Vertical’;
end

%% —————- 5. Apply ONE Fault to All Layers —————-
z_layers = z_inv;

for L = 1:N_layers
if strcmp(MainFault.type,’Reverse’)
z_layers(idx_fault:end, L:end) = z_layers(idx_fault:end, L:end) + MainFault.throw;

elseif strcmp(MainFault.type,’Normal’)
z_layers(idx_fault:end, L:end) = z_layers(idx_fault:end, L:end) – MainFault.throw;

else
% Vertical → no vertical shift
end
end

%% —————- 6. Plot Depth ————————
figure; hold on;
for i = 1:N_layers
plot(x, z_layers(:,i),’LineWidth’,2);
end
set(gca,’YDir’,’reverse’);
grid on;
title(‘Depth with Single Fault’);
xlabel(‘Distance (km)’);
ylabel(‘Depth (km)’);
legend(arrayfun(@(k) sprintf(‘Layer %d’,k),1:N_layers,’UniformOutput’,false));

%% —————- 7. Plot Single Fault Plane ————————
z_max = max(z_layers(:));

if strcmp(MainFault.type,’Vertical’)
plot([MainFault.x MainFault.x],[0 z_max],’r–‘,’LineWidth’,2);
else
dx = z_max / tand(MainFault.dip);

if MainFault.dip > 0
x2 = MainFault.x – dx;
else
x2 = MainFault.x + dx;
end

plot([MainFault.x x2],[0 z_max],’r–‘,’LineWidth’,2);
end

%% —————- 8. Dip Line from Surface ————————
figure; hold on;

for i = 1:N_layers
plot(x, z_layers(:,i),’LineWidth’,2);
end

set(gca,’YDir’,’reverse’);
grid on;
title(‘Single Fault Dip Line’);
xlabel(‘Distance (km)’);
ylabel(‘Depth (km)’);

z1 = max(z_layers(:,1));
dip = MainFault.dip;
x0 = MainFault.x;

if abs(dip) > 89
x1 = x0;
else
x1 = x0 + z1 / tand(dip);
end

plot([x0 x1],[0 z1],’r–‘,’LineWidth’,2);
text((x0+x1)/2,0.3,’Main Fault’,’Color’,’r’);

%% —————- 9. Geological Section ————————
figure; hold on;

colors = lines(N_layers);

for i = N_layers:-1:1
if i == 1
top = zeros(size(x));
else
top = z_layers(:,i-1);
end

bot = z_layers(:,i);

fill([x;flipud(x)], [top;flipud(bot)], colors(i,:), …
‘EdgeColor’,’k’,’FaceAlpha’,0.6);
end

% رسم الصدع
if strcmp(MainFault.type,’Vertical’)
plot([MainFault.x MainFault.x],[0 z_max],’k–‘,’LineWidth’,2);
else
dx = z_max / tand(MainFault.dip);

if MainFault.dip > 0
x2 = MainFault.x – dx;
else
x2 = MainFault.x + dx;
end

plot([MainFault.x x2],[0 z_max],’k–‘,’LineWidth’,2);
end

set(gca,’YDir’,’reverse’);
xlabel(‘Distance (km)’);
ylabel(‘Depth (km)’);
title(‘Geological Cross Section with Single Fault’);

legend(arrayfun(@(i) sprintf(‘Layer %d’,i),1:N_layers,’UniformOutput’,false));
we use the following paramters:
Enter number of layers: 3
Density of layer 1: 2.20
Density of layer 2: 2.25
Density of layer 3: 2.30
Basement density: 2.67Dear all
I need help to add an algoritm or modified the exsit one to get the figures annexed in file:the following is my code:
clc; clear; close all;

%% —————- 1. Load Data ————————————
filename = ‘ThreeFaultModel_Modified.xlsx’;
data = xlsread(filename);

x = data(:,1);
g_Bouguer = data(:,2);
x = x(:); g_Bouguer = g_Bouguer(:);

%% —————- 2. User Inputs ———————————
N_layers = input(‘Enter number of layers: ‘);

rho_profiles = zeros(1, N_layers);
for i = 1:N_layers
rho_profiles(i) = input([‘Density of layer ‘ num2str(i) ‘: ‘]);
end

rho_basement = input(‘Basement density: ‘);
rho_contrasts = rho_profiles – rho_basement;

%% —————- 3. Inversion ————————
G = 6.67e-3;

z_inv = bsxfun(@rdivide, g_Bouguer, (2*pi*G*rho_contrasts));

%% —————- 4. Detect ONE Main Fault ————————
VG = gradient(z_inv(:,1), x);

% اختيار أقوى تغير (fault)
[~, idx_fault] = max(abs(VG));

MainFault.x = x(idx_fault);
MainFault.dip = atan2d(VG(idx_fault),1); % تقدير تقريبي
MainFault.throw = max(z_inv(:,1)) * 0.3; % تقدير بسيط
MainFault.type = ‘Normal’;

if MainFault.dip > 0
MainFault.type = ‘Reverse’;
end
if abs(MainFault.dip) > 85
MainFault.type = ‘Vertical’;
end

%% —————- 5. Apply ONE Fault to All Layers —————-
z_layers = z_inv;

for L = 1:N_layers
if strcmp(MainFault.type,’Reverse’)
z_layers(idx_fault:end, L:end) = z_layers(idx_fault:end, L:end) + MainFault.throw;

elseif strcmp(MainFault.type,’Normal’)
z_layers(idx_fault:end, L:end) = z_layers(idx_fault:end, L:end) – MainFault.throw;

else
% Vertical → no vertical shift
end
end

%% —————- 6. Plot Depth ————————
figure; hold on;
for i = 1:N_layers
plot(x, z_layers(:,i),’LineWidth’,2);
end
set(gca,’YDir’,’reverse’);
grid on;
title(‘Depth with Single Fault’);
xlabel(‘Distance (km)’);
ylabel(‘Depth (km)’);
legend(arrayfun(@(k) sprintf(‘Layer %d’,k),1:N_layers,’UniformOutput’,false));

%% —————- 7. Plot Single Fault Plane ————————
z_max = max(z_layers(:));

if strcmp(MainFault.type,’Vertical’)
plot([MainFault.x MainFault.x],[0 z_max],’r–‘,’LineWidth’,2);
else
dx = z_max / tand(MainFault.dip);

if MainFault.dip > 0
x2 = MainFault.x – dx;
else
x2 = MainFault.x + dx;
end

plot([MainFault.x x2],[0 z_max],’r–‘,’LineWidth’,2);
end

%% —————- 8. Dip Line from Surface ————————
figure; hold on;

for i = 1:N_layers
plot(x, z_layers(:,i),’LineWidth’,2);
end

set(gca,’YDir’,’reverse’);
grid on;
title(‘Single Fault Dip Line’);
xlabel(‘Distance (km)’);
ylabel(‘Depth (km)’);

z1 = max(z_layers(:,1));
dip = MainFault.dip;
x0 = MainFault.x;

if abs(dip) > 89
x1 = x0;
else
x1 = x0 + z1 / tand(dip);
end

plot([x0 x1],[0 z1],’r–‘,’LineWidth’,2);
text((x0+x1)/2,0.3,’Main Fault’,’Color’,’r’);

%% —————- 9. Geological Section ————————
figure; hold on;

colors = lines(N_layers);

for i = N_layers:-1:1
if i == 1
top = zeros(size(x));
else
top = z_layers(:,i-1);
end

bot = z_layers(:,i);

fill([x;flipud(x)], [top;flipud(bot)], colors(i,:), …
‘EdgeColor’,’k’,’FaceAlpha’,0.6);
end

% رسم الصدع
if strcmp(MainFault.type,’Vertical’)
plot([MainFault.x MainFault.x],[0 z_max],’k–‘,’LineWidth’,2);
else
dx = z_max / tand(MainFault.dip);

if MainFault.dip > 0
x2 = MainFault.x – dx;
else
x2 = MainFault.x + dx;
end

plot([MainFault.x x2],[0 z_max],’k–‘,’LineWidth’,2);
end

set(gca,’YDir’,’reverse’);
xlabel(‘Distance (km)’);
ylabel(‘Depth (km)’);
title(‘Geological Cross Section with Single Fault’);

legend(arrayfun(@(i) sprintf(‘Layer %d’,i),1:N_layers,’UniformOutput’,false));
we use the following paramters:
Enter number of layers: 3
Density of layer 1: 2.20
Density of layer 2: 2.25
Density of layer 3: 2.30
Basement density: 2.67 Dear all
I need help to add an algoritm or modified the exsit one to get the figures annexed in file:the following is my code:
clc; clear; close all;

%% —————- 1. Load Data ————————————
filename = ‘ThreeFaultModel_Modified.xlsx’;
data = xlsread(filename);

x = data(:,1);
g_Bouguer = data(:,2);
x = x(:); g_Bouguer = g_Bouguer(:);

%% —————- 2. User Inputs ———————————
N_layers = input(‘Enter number of layers: ‘);

rho_profiles = zeros(1, N_layers);
for i = 1:N_layers
rho_profiles(i) = input([‘Density of layer ‘ num2str(i) ‘: ‘]);
end

rho_basement = input(‘Basement density: ‘);
rho_contrasts = rho_profiles – rho_basement;

%% —————- 3. Inversion ————————
G = 6.67e-3;

z_inv = bsxfun(@rdivide, g_Bouguer, (2*pi*G*rho_contrasts));

%% —————- 4. Detect ONE Main Fault ————————
VG = gradient(z_inv(:,1), x);

% اختيار أقوى تغير (fault)
[~, idx_fault] = max(abs(VG));

MainFault.x = x(idx_fault);
MainFault.dip = atan2d(VG(idx_fault),1); % تقدير تقريبي
MainFault.throw = max(z_inv(:,1)) * 0.3; % تقدير بسيط
MainFault.type = ‘Normal’;

if MainFault.dip > 0
MainFault.type = ‘Reverse’;
end
if abs(MainFault.dip) > 85
MainFault.type = ‘Vertical’;
end

%% —————- 5. Apply ONE Fault to All Layers —————-
z_layers = z_inv;

for L = 1:N_layers
if strcmp(MainFault.type,’Reverse’)
z_layers(idx_fault:end, L:end) = z_layers(idx_fault:end, L:end) + MainFault.throw;

elseif strcmp(MainFault.type,’Normal’)
z_layers(idx_fault:end, L:end) = z_layers(idx_fault:end, L:end) – MainFault.throw;

else
% Vertical → no vertical shift
end
end

%% —————- 6. Plot Depth ————————
figure; hold on;
for i = 1:N_layers
plot(x, z_layers(:,i),’LineWidth’,2);
end
set(gca,’YDir’,’reverse’);
grid on;
title(‘Depth with Single Fault’);
xlabel(‘Distance (km)’);
ylabel(‘Depth (km)’);
legend(arrayfun(@(k) sprintf(‘Layer %d’,k),1:N_layers,’UniformOutput’,false));

%% —————- 7. Plot Single Fault Plane ————————
z_max = max(z_layers(:));

if strcmp(MainFault.type,’Vertical’)
plot([MainFault.x MainFault.x],[0 z_max],’r–‘,’LineWidth’,2);
else
dx = z_max / tand(MainFault.dip);

if MainFault.dip > 0
x2 = MainFault.x – dx;
else
x2 = MainFault.x + dx;
end

plot([MainFault.x x2],[0 z_max],’r–‘,’LineWidth’,2);
end

%% —————- 8. Dip Line from Surface ————————
figure; hold on;

for i = 1:N_layers
plot(x, z_layers(:,i),’LineWidth’,2);
end

set(gca,’YDir’,’reverse’);
grid on;
title(‘Single Fault Dip Line’);
xlabel(‘Distance (km)’);
ylabel(‘Depth (km)’);

z1 = max(z_layers(:,1));
dip = MainFault.dip;
x0 = MainFault.x;

if abs(dip) > 89
x1 = x0;
else
x1 = x0 + z1 / tand(dip);
end

plot([x0 x1],[0 z1],’r–‘,’LineWidth’,2);
text((x0+x1)/2,0.3,’Main Fault’,’Color’,’r’);

%% —————- 9. Geological Section ————————
figure; hold on;

colors = lines(N_layers);

for i = N_layers:-1:1
if i == 1
top = zeros(size(x));
else
top = z_layers(:,i-1);
end

bot = z_layers(:,i);

fill([x;flipud(x)], [top;flipud(bot)], colors(i,:), …
‘EdgeColor’,’k’,’FaceAlpha’,0.6);
end

% رسم الصدع
if strcmp(MainFault.type,’Vertical’)
plot([MainFault.x MainFault.x],[0 z_max],’k–‘,’LineWidth’,2);
else
dx = z_max / tand(MainFault.dip);

if MainFault.dip > 0
x2 = MainFault.x – dx;
else
x2 = MainFault.x + dx;
end

plot([MainFault.x x2],[0 z_max],’k–‘,’LineWidth’,2);
end

set(gca,’YDir’,’reverse’);
xlabel(‘Distance (km)’);
ylabel(‘Depth (km)’);
title(‘Geological Cross Section with Single Fault’);

legend(arrayfun(@(i) sprintf(‘Layer %d’,i),1:N_layers,’UniformOutput’,false));
we use the following paramters:
Enter number of layers: 3
Density of layer 1: 2.20
Density of layer 2: 2.25
Density of layer 3: 2.30
Basement density: 2.67 matlab, drawing, plane MATLAB Answers — New Questions

​

I’m trying to switch from the old “black” Simcape Specialized Power System library to the new “blue” Simcape library. I’m using the phasor solution and the fast calculation method, but the problem lies with the phasor solver itself. The solver resets the Jacobian matrix much more frequently than the Specilaized Power library solver. Any tips on how to reduce the frequency of these resets?
See attached report from Simulink Profiler:I’m trying to switch from the old “black” Simcape Specialized Power System library to the new “blue” Simcape library. I’m using the phasor solution and the fast calculation method, but the problem lies with the phasor solver itself. The solver resets the Jacobian matrix much more frequently than the Specilaized Power library solver. Any tips on how to reduce the frequency of these resets?
See attached report from Simulink Profiler: I’m trying to switch from the old “black” Simcape Specialized Power System library to the new “blue” Simcape library. I’m using the phasor solution and the fast calculation method, but the problem lies with the phasor solver itself. The solver resets the Jacobian matrix much more frequently than the Specilaized Power library solver. Any tips on how to reduce the frequency of these resets?
See attached report from Simulink Profiler: reset, jacobian MATLAB Answers — New Questions

​

Hello to fellow MATLAB users. I am studying electrical engineering and not so familiar with MATLAB and Simulink. Therefore I need your help.
I want to integrate a MMC system into IEEE 9 bus system to study how fault current behaves when an AC transmission line is replaced with a HVDC link. More specifically I want to integrate simscapeelectrical/ModularMultilevelConverterHVDCTransExample between bus 4 and bus 6 in simscapeelectrical/IEEE9BusSystemExample. However, I am at a dead end right now, no matter what I try I can’t get it right. I’d appreciate if you could guide me on how to tackle this problem.Hello to fellow MATLAB users. I am studying electrical engineering and not so familiar with MATLAB and Simulink. Therefore I need your help.
I want to integrate a MMC system into IEEE 9 bus system to study how fault current behaves when an AC transmission line is replaced with a HVDC link. More specifically I want to integrate simscapeelectrical/ModularMultilevelConverterHVDCTransExample between bus 4 and bus 6 in simscapeelectrical/IEEE9BusSystemExample. However, I am at a dead end right now, no matter what I try I can’t get it right. I’d appreciate if you could guide me on how to tackle this problem. Hello to fellow MATLAB users. I am studying electrical engineering and not so familiar with MATLAB and Simulink. Therefore I need your help.
I want to integrate a MMC system into IEEE 9 bus system to study how fault current behaves when an AC transmission line is replaced with a HVDC link. More specifically I want to integrate simscapeelectrical/ModularMultilevelConverterHVDCTransExample between bus 4 and bus 6 in simscapeelectrical/IEEE9BusSystemExample. However, I am at a dead end right now, no matter what I try I can’t get it right. I’d appreciate if you could guide me on how to tackle this problem. mmc, hvdc, ieee 9 bus, ac transmission MATLAB Answers — New Questions

​

Suppose there are two square symmetric matrices [K] and [M]. Since my work is related with structural analysis so they are typically stiffness and mass matrices. I am doing wave propagation study for a narrow band input load. In frequency domain, load amplitude is significant only between frequency [omega1 omega2]. So I am interested to find all eigen value and corresponding eigen vector only in this range.

The eigen value problem statement is
[K]=lambda[M]Suppose there are two square symmetric matrices [K] and [M]. Since my work is related with structural analysis so they are typically stiffness and mass matrices. I am doing wave propagation study for a narrow band input load. In frequency domain, load amplitude is significant only between frequency [omega1 omega2]. So I am interested to find all eigen value and corresponding eigen vector only in this range.

The eigen value problem statement is
[K]=lambda[M] Suppose there are two square symmetric matrices [K] and [M]. Since my work is related with structural analysis so they are typically stiffness and mass matrices. I am doing wave propagation study for a narrow band input load. In frequency domain, load amplitude is significant only between frequency [omega1 omega2]. So I am interested to find all eigen value and corresponding eigen vector only in this range.

The eigen value problem statement is
[K]=lambda[M] all eigen value between given range MATLAB Answers — New Questions

​

I have a model that I plan on deploying with Simulink Compiler. I would like to stream the inputs and outputs to the model, for example:Stream inputs/outputs with TCP/UDPPublish subscribe with ROS OPC client-server communicationRead from or write to a file or databaseStream to a live output visualization
I tried putting the input and output handling inside the model itself, with specific I/O blocks however I ran into problems with blocks not being supported for Rapid Accelerator mode. What is the recommended method to do this?I have a model that I plan on deploying with Simulink Compiler. I would like to stream the inputs and outputs to the model, for example:Stream inputs/outputs with TCP/UDPPublish subscribe with ROS OPC client-server communicationRead from or write to a file or databaseStream to a live output visualization
I tried putting the input and output handling inside the model itself, with specific I/O blocks however I ran into problems with blocks not being supported for Rapid Accelerator mode. What is the recommended method to do this? I have a model that I plan on deploying with Simulink Compiler. I would like to stream the inputs and outputs to the model, for example:Stream inputs/outputs with TCP/UDPPublish subscribe with ROS OPC client-server communicationRead from or write to a file or databaseStream to a live output visualization
I tried putting the input and output handling inside the model itself, with specific I/O blocks however I ran into problems with blocks not being supported for Rapid Accelerator mode. What is the recommended method to do this? simulinkcompiler, deployment, simulink, compiler, io MATLAB Answers — New Questions

​

In addition to a shared ylabel on the left hand-side of a figure, I want to put a shared ylabel on the right hand-side of the tiledlayout, when also using yyaxis. How can I achieve this? I have prepared the following MWE:
figure
t = tiledlayout(4,1);

for i = 1:4
nexttile
title("Tile"+i)

yyaxis left
plot(rand(1,10))

yyaxis right
plot(rand(1,10))
end

title(t,"Tiles")
xlabel(t,"x")
ylabel(t,"y left")
% ylabel(t,"y right")
Thanks in advance!

Edit:
My yticklabels on the left as well as on the right hand-side are relatively long, therefore, both shared ylabels need to factor the necessary distance in. The shared ylabel on the left hand-side does this automatically, the one on the right hand-side should do the same. I have updated the MWE (unfortunately, it now acts a bit buggy but it should illustrate the point, nonetheless):
figure
t = tiledlayout(4,1);

longYTickLabels_left = ["negative yticklabel left" "0" "positive yticklabel left" ];%edit: added
longYTickLabels_right = ["negative yticklabel right" "0" "positive yticklabel right"];%edit: added
for i = 1:4
nexttile
title("Tile"+i)

yyaxis left
plot(rand(1,10))
yticklabels(longYTickLabels_left)%edit: added

yyaxis right
plot(rand(1,10))
yticklabels(longYTickLabels_right)%edit: added
end

title(t,"Tiles")
xlabel(t,"x")
ylabel(t,"y left")
% ylabel(t,"y right")In addition to a shared ylabel on the left hand-side of a figure, I want to put a shared ylabel on the right hand-side of the tiledlayout, when also using yyaxis. How can I achieve this? I have prepared the following MWE:
figure
t = tiledlayout(4,1);

for i = 1:4
nexttile
title("Tile"+i)

yyaxis left
plot(rand(1,10))

yyaxis right
plot(rand(1,10))
end

title(t,"Tiles")
xlabel(t,"x")
ylabel(t,"y left")
% ylabel(t,"y right")
Thanks in advance!

Edit:
My yticklabels on the left as well as on the right hand-side are relatively long, therefore, both shared ylabels need to factor the necessary distance in. The shared ylabel on the left hand-side does this automatically, the one on the right hand-side should do the same. I have updated the MWE (unfortunately, it now acts a bit buggy but it should illustrate the point, nonetheless):
figure
t = tiledlayout(4,1);

longYTickLabels_left = ["negative yticklabel left" "0" "positive yticklabel left" ];%edit: added
longYTickLabels_right = ["negative yticklabel right" "0" "positive yticklabel right"];%edit: added
for i = 1:4
nexttile
title("Tile"+i)

yyaxis left
plot(rand(1,10))
yticklabels(longYTickLabels_left)%edit: added

yyaxis right
plot(rand(1,10))
yticklabels(longYTickLabels_right)%edit: added
end

title(t,"Tiles")
xlabel(t,"x")
ylabel(t,"y left")
% ylabel(t,"y right") In addition to a shared ylabel on the left hand-side of a figure, I want to put a shared ylabel on the right hand-side of the tiledlayout, when also using yyaxis. How can I achieve this? I have prepared the following MWE:
figure
t = tiledlayout(4,1);

for i = 1:4
nexttile
title("Tile"+i)

yyaxis left
plot(rand(1,10))

yyaxis right
plot(rand(1,10))
end

title(t,"Tiles")
xlabel(t,"x")
ylabel(t,"y left")
% ylabel(t,"y right")
Thanks in advance!

Edit:
My yticklabels on the left as well as on the right hand-side are relatively long, therefore, both shared ylabels need to factor the necessary distance in. The shared ylabel on the left hand-side does this automatically, the one on the right hand-side should do the same. I have updated the MWE (unfortunately, it now acts a bit buggy but it should illustrate the point, nonetheless):
figure
t = tiledlayout(4,1);

longYTickLabels_left = ["negative yticklabel left" "0" "positive yticklabel left" ];%edit: added
longYTickLabels_right = ["negative yticklabel right" "0" "positive yticklabel right"];%edit: added
for i = 1:4
nexttile
title("Tile"+i)

yyaxis left
plot(rand(1,10))
yticklabels(longYTickLabels_left)%edit: added

yyaxis right
plot(rand(1,10))
yticklabels(longYTickLabels_right)%edit: added
end

title(t,"Tiles")
xlabel(t,"x")
ylabel(t,"y left")
% ylabel(t,"y right") tiledlayout, yyaxis, ylabel, figure MATLAB Answers — New Questions

​

Geospectrum M36-600 with porpoise datalogger was used to capture noise. The code and respective output are given below. I want to know what is the output format of audioread? Is it normalized or volts or Pa?
CODE:
info = audioinfo(‘D:NIOTDSMmatlab codeNoiseMatlab PC4.06.2025 HydrophoneVFDNear Motor20250604154138 199-203s.wav’);
disp(info)
[y,Fs] = audioread(‘D:NIOTDSMmatlab codeNoiseMatlab PC4.06.2025 HydrophoneVFDNear Motor20250604154138 199-203s.wav’); % default: scaled floating-point
[yN,FsN] = audioread(‘D:NIOTDSMmatlab codeNoiseMatlab PC4.06.2025 HydrophoneVFDNear Motor20250604154138 199-203s.wav’,"native"); % native format when available
class(y)
min(y)
max(y)
OUTPUT:
class(yN)NoiseMatlab PC4.06.2025 HydrophoneVFDNear Motor20250604154138 199-203s.wav’
CompressionMethod: ‘Uncompressed’
NumChannels: 1
SampleRate: 32000
TotalSamples: 129024
Duration: 4.0320
Title: []
Comment: []
Artist: []
BitsPerSample: 16
ans = ‘double’
ans = -1.5259e-04
ans = 1.5259e-04
ans = ‘int16’Geospectrum M36-600 with porpoise datalogger was used to capture noise. The code and respective output are given below. I want to know what is the output format of audioread? Is it normalized or volts or Pa?
CODE:
info = audioinfo(‘D:NIOTDSMmatlab codeNoiseMatlab PC4.06.2025 HydrophoneVFDNear Motor20250604154138 199-203s.wav’);
disp(info)
[y,Fs] = audioread(‘D:NIOTDSMmatlab codeNoiseMatlab PC4.06.2025 HydrophoneVFDNear Motor20250604154138 199-203s.wav’); % default: scaled floating-point
[yN,FsN] = audioread(‘D:NIOTDSMmatlab codeNoiseMatlab PC4.06.2025 HydrophoneVFDNear Motor20250604154138 199-203s.wav’,"native"); % native format when available
class(y)
min(y)
max(y)
OUTPUT:
class(yN)NoiseMatlab PC4.06.2025 HydrophoneVFDNear Motor20250604154138 199-203s.wav’
CompressionMethod: ‘Uncompressed’
NumChannels: 1
SampleRate: 32000
TotalSamples: 129024
Duration: 4.0320
Title: []
Comment: []
Artist: []
BitsPerSample: 16
ans = ‘double’
ans = -1.5259e-04
ans = 1.5259e-04
ans = ‘int16’ Geospectrum M36-600 with porpoise datalogger was used to capture noise. The code and respective output are given below. I want to know what is the output format of audioread? Is it normalized or volts or Pa?
CODE:
info = audioinfo(‘D:NIOTDSMmatlab codeNoiseMatlab PC4.06.2025 HydrophoneVFDNear Motor20250604154138 199-203s.wav’);
disp(info)
[y,Fs] = audioread(‘D:NIOTDSMmatlab codeNoiseMatlab PC4.06.2025 HydrophoneVFDNear Motor20250604154138 199-203s.wav’); % default: scaled floating-point
[yN,FsN] = audioread(‘D:NIOTDSMmatlab codeNoiseMatlab PC4.06.2025 HydrophoneVFDNear Motor20250604154138 199-203s.wav’,"native"); % native format when available
class(y)
min(y)
max(y)
OUTPUT:
class(yN)NoiseMatlab PC4.06.2025 HydrophoneVFDNear Motor20250604154138 199-203s.wav’
CompressionMethod: ‘Uncompressed’
NumChannels: 1
SampleRate: 32000
TotalSamples: 129024
Duration: 4.0320
Title: []
Comment: []
Artist: []
BitsPerSample: 16
ans = ‘double’
ans = -1.5259e-04
ans = 1.5259e-04
ans = ‘int16’ audioread, hydrophone, porpoisedatalogger MATLAB Answers — New Questions

​

Hello,

I am working with Deep Learning HDL Toolbox on a custom reference design
with the Xilinx ZCU111 RFSoC board. I am able to successfully compile the network,
but I am encountering a deployment error.

Setup: – Board: ZCU111 RFSoC – Interface: PS GEM Ethernet – Reference design:
Custom (based on AXI-Stream DDR Memory Access : 3-AXIM) – Tool versions:
Vivado 2024.1, MATLAB (Deep Learning HDL Toolbox)

Workflow: I compile and deploy the network using: 1. compile(hW) 2.
deploy(hW) 3. predict(…)

Problem: The FPGA is programmed successfully, and the system reboots
correctly: – SSH connection is restored – Ping works

However, during deployment/predict, I get the following error on MATLAB:

Connection to the bitstream is no longer valid caused by error: Data
size mismatch.

Observations: – Bitstream programming is completed successfully – Device
tree is loaded and system boots – The error happens after deployment,
during runtime communication with FPGA.

Device Tree Concern: I suspect that the issue may be related to my device
tree definitions, especially: – dlprocessor IP – AXI stream to
memory-mapped interface (AXIS2AXIM / AXI2SMM) – DMA nodes (MM2S / S2MM)

Possible causes: Incorrect child node definitions

Questions: 1. What are the common causes of “Data size mismatch” in Deep
Learning HDL deployments? 2. Can this error be caused by incorrect
device tree configuration ? 3. Are there specific DTB
requirements for dlprocessor, AXIS2AXIM, and DMA nodes? 4. How can I
verify MATLAB runtime correctly binds to DTB nodes?

Also is there any official or working example of devicetree_dlhdl.dtb for:
Deep Learning HDL Toolbox
AXI-Stream DDR Memory Access (3-AXIM) reference design
ZCU111 (or similar Zynq UltraScale+ platforms)
I am especially interested in correct definitions for:
dlprocessor
AXIS2AXIM / AXI2SMM
DMA nodes (MM2S / S2MM)
mathworks-specific properties (mwipcore, channels, etc.)
If anyone has a working DTB or can point to an example (documentation, repo, or generated output), it would be very helpful.
Thanks!Hello,

I am working with Deep Learning HDL Toolbox on a custom reference design
with the Xilinx ZCU111 RFSoC board. I am able to successfully compile the network,
but I am encountering a deployment error.

Setup: – Board: ZCU111 RFSoC – Interface: PS GEM Ethernet – Reference design:
Custom (based on AXI-Stream DDR Memory Access : 3-AXIM) – Tool versions:
Vivado 2024.1, MATLAB (Deep Learning HDL Toolbox)

Workflow: I compile and deploy the network using: 1. compile(hW) 2.
deploy(hW) 3. predict(…)

Problem: The FPGA is programmed successfully, and the system reboots
correctly: – SSH connection is restored – Ping works

However, during deployment/predict, I get the following error on MATLAB:

Connection to the bitstream is no longer valid caused by error: Data
size mismatch.

Observations: – Bitstream programming is completed successfully – Device
tree is loaded and system boots – The error happens after deployment,
during runtime communication with FPGA.

Device Tree Concern: I suspect that the issue may be related to my device
tree definitions, especially: – dlprocessor IP – AXI stream to
memory-mapped interface (AXIS2AXIM / AXI2SMM) – DMA nodes (MM2S / S2MM)

Possible causes: Incorrect child node definitions

Questions: 1. What are the common causes of “Data size mismatch” in Deep
Learning HDL deployments? 2. Can this error be caused by incorrect
device tree configuration ? 3. Are there specific DTB
requirements for dlprocessor, AXIS2AXIM, and DMA nodes? 4. How can I
verify MATLAB runtime correctly binds to DTB nodes?

Also is there any official or working example of devicetree_dlhdl.dtb for:
Deep Learning HDL Toolbox
AXI-Stream DDR Memory Access (3-AXIM) reference design
ZCU111 (or similar Zynq UltraScale+ platforms)
I am especially interested in correct definitions for:
dlprocessor
AXIS2AXIM / AXI2SMM
DMA nodes (MM2S / S2MM)
mathworks-specific properties (mwipcore, channels, etc.)
If anyone has a working DTB or can point to an example (documentation, repo, or generated output), it would be very helpful.
Thanks! Hello,

I am working with Deep Learning HDL Toolbox on a custom reference design
with the Xilinx ZCU111 RFSoC board. I am able to successfully compile the network,
but I am encountering a deployment error.

Setup: – Board: ZCU111 RFSoC – Interface: PS GEM Ethernet – Reference design:
Custom (based on AXI-Stream DDR Memory Access : 3-AXIM) – Tool versions:
Vivado 2024.1, MATLAB (Deep Learning HDL Toolbox)

Workflow: I compile and deploy the network using: 1. compile(hW) 2.
deploy(hW) 3. predict(…)

Problem: The FPGA is programmed successfully, and the system reboots
correctly: – SSH connection is restored – Ping works

However, during deployment/predict, I get the following error on MATLAB:

Connection to the bitstream is no longer valid caused by error: Data
size mismatch.

Observations: – Bitstream programming is completed successfully – Device
tree is loaded and system boots – The error happens after deployment,
during runtime communication with FPGA.

Device Tree Concern: I suspect that the issue may be related to my device
tree definitions, especially: – dlprocessor IP – AXI stream to
memory-mapped interface (AXIS2AXIM / AXI2SMM) – DMA nodes (MM2S / S2MM)

Possible causes: Incorrect child node definitions

Questions: 1. What are the common causes of “Data size mismatch” in Deep
Learning HDL deployments? 2. Can this error be caused by incorrect
device tree configuration ? 3. Are there specific DTB
requirements for dlprocessor, AXIS2AXIM, and DMA nodes? 4. How can I
verify MATLAB runtime correctly binds to DTB nodes?

Also is there any official or working example of devicetree_dlhdl.dtb for:
Deep Learning HDL Toolbox
AXI-Stream DDR Memory Access (3-AXIM) reference design
ZCU111 (or similar Zynq UltraScale+ platforms)
I am especially interested in correct definitions for:
dlprocessor
AXIS2AXIM / AXI2SMM
DMA nodes (MM2S / S2MM)
mathworks-specific properties (mwipcore, channels, etc.)
If anyone has a working DTB or can point to an example (documentation, repo, or generated output), it would be very helpful.
Thanks! deep learning, cnn, deep learning hdl toolbox, vivado, zcu111 rfsoc board, fpga MATLAB Answers — New Questions

​

According to the previous thread, MATLAB can be made to open .m files by default in Ubuntu by editing the matlab.desktop file (usually in /usr/share/applications) and changing:
Exec=matlab -desktop
to
Exec=matlab -desktop -r "edit %f"
https://uk.mathworks.com/matlabcentral/answers/565784-defautl-to-open-m-files-in-matlab-linux
This has the side effect that opening MATLAB from its icon causes an empty editor window to be open. Can anyone advise how to avoid this? It looks like using X-Ayatana-Desktop-Shortcuts may help, but I cannot figure out how to make just opening the command window the default and opening the editor to happen only if a file is specified.According to the previous thread, MATLAB can be made to open .m files by default in Ubuntu by editing the matlab.desktop file (usually in /usr/share/applications) and changing:
Exec=matlab -desktop
to
Exec=matlab -desktop -r "edit %f"
https://uk.mathworks.com/matlabcentral/answers/565784-defautl-to-open-m-files-in-matlab-linux
This has the side effect that opening MATLAB from its icon causes an empty editor window to be open. Can anyone advise how to avoid this? It looks like using X-Ayatana-Desktop-Shortcuts may help, but I cannot figure out how to make just opening the command window the default and opening the editor to happen only if a file is specified. According to the previous thread, MATLAB can be made to open .m files by default in Ubuntu by editing the matlab.desktop file (usually in /usr/share/applications) and changing:
Exec=matlab -desktop
to
Exec=matlab -desktop -r "edit %f"
https://uk.mathworks.com/matlabcentral/answers/565784-defautl-to-open-m-files-in-matlab-linux
This has the side effect that opening MATLAB from its icon causes an empty editor window to be open. Can anyone advise how to avoid this? It looks like using X-Ayatana-Desktop-Shortcuts may help, but I cannot figure out how to make just opening the command window the default and opening the editor to happen only if a file is specified. linux, ubuntu, x-ayatana-desktop-shortcuts MATLAB Answers — New Questions

​