Issue with InputVisibility for lsimplot

I am trying to generate a plot of a response of a StateSpace System (1 Input, 5 Outputs, with Outputs 2,3 and 4 of interest) to an predefined input. When using the lsimplot() function, it automatically displays the input in every subplots what makes it quiet hard to see the acutal response at its magnitude is significantly smaller.

To avoid removing it each time manually in the figure, i tried to manipulate the InputVisible-Option.

figure(1)
plot1 = lsimplot(dyn_sys(2:4),u_sim,t_sim);
plot1.InputVisible = {'off'}

But in this case the response is not plotted at all (emtpy figure, only showing the axis labels). Any other syntax like

plot1.InputVisible = 'off'

or

plot1.InputVisible = false

resulted in an Error when running the file.

"Cell array of character vectors may only contain character vectors and numeric matrices.

Error in XXX

plot1.InputVisible = 'off' "

Note: I recognised that the by default the "InputVisible"-Parameter is not "on" or "true" as I expected but empty.

Has anybody encountered the same problem and knows how to resolve it?

Answer 1

[Star Strider]

It would probably help to have the omitted parts of your code.

What you want to do works here (R2025b).

A work-around would be to recover the data you want, and plot it separately. In order to get that information, it will be necessary to dive deeply into the lsimplot properties.

Using an example from the lsimplot documentation, this shows one approach --

A = [-2-2i -2;1 0];
B = [2;0];
C = [0 0.5+2.5i];
D = 0;
sys = ss(A,B,C,D);

figure
[u,t] = gensig("square",4,12);
lp = lsimplot(sys,u,t);
lp.InputVisible='off';

figure
[u,t] = gensig("square",4,12);
lp = lsimplot(sys,u,t);

●

% get(lp)
Kids = lp.Children;
% get(Kids)
GKids = Kids.Children;
% get(GKids)
GGKids = GKids.Children;
% get(GGKids)
GGGKids = GGKids.Children

GGGKids = 
  5×1 graphics array:

  Line     (SimulationResponseLine)
  Line     (TimeImaginaryResponseLine)
  Patch    (TimeImaginaryMarkerPatch)
  Line     (TimeMagnitudeResponseLine)
  Line     (SimulationInputLine)

Line1 = GGGKids(1)

Line1 = 
  Line (SimulationResponseLine) with properties:

              Color: [0.0660 0.4430 0.7450]
          LineStyle: '-'
          LineWidth: 0.5000
             Marker: 'none'
         MarkerSize: 6
    MarkerFaceColor: 'none'
              XData: [0 0.0625 0.1250 0.1875 0.2500 0.3125 0.3750 0.4375 0.5000 0.5625 0.6250 0.6875 0.7500 0.8125 0.8750 0.9375 1 1.0625 1.1250 1.1875 1.2500 … ] (1×193 double)
              YData: [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 0 0 0 0 0 0.0023 0.0100 0.0243 0.0458 0.0746 0.1104 0.1529 0.2013 0.2547 0.3122 … ] (1×193 double)

  Use GET to show all properties

Line3 = GGGKids(4)

Line3 = 
  Line (TimeMagnitudeResponseLine) with properties:

              Color: [0.0660 0.4430 0.7450]
          LineStyle: '-'
          LineWidth: 0.5000
             Marker: 'none'
         MarkerSize: 6
    MarkerFaceColor: 'none'
              XData: [0 0.0625 0.1250 0.1875 0.2500 0.3125 0.3750 0.4375 0.5000 0.5625 0.6250 0.6875 0.7500 0.8125 0.8750 0.9375 1 1.0625 1.1250 1.1875 1.2500 … ] (1×193 double)
              YData: [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 0 0 0 0 0 0.0095 0.0366 0.0787 0.1336 0.1991 0.2734 0.3544 0.4405 0.5301 0.6219 … ] (1×193 double)

  Use GET to show all properties

figure
plot(Line1.XData, Line1.YData, DisplayName="Simulation Response")
hold on
plot(Line3.XData, Line3.YData, DisplayName="Time-Magnitude Response")
hold off
legend(Location='best')

I commented-out most of the get calls. Uncomment them to see what they reveal.

.

EDIT -- (17 Dec 2025 at 14:38)

Clarified explanation.

.

[Hannes]

Thanks for the detailed response. When trying to run your example, I get the error "Undefined function 'Children' for input arguments of type 'resppack.simplot'".

Anyways, I seems to me that the method you suggest only extracts the datasets, consisting of time and y-Value, of each line of the plot, while losing information about the name of the corresponding output. This I could also accomplish with y = lsim(sys,u,t). Or do I miss anything?