Show results of ensemble run using 2-D or 3-D plots
sbioensembleplot(
simdataObj
)
sbioensembleplot(simdataObj
, Names
)
sbioensembleplot(simdataObj
, Names
, Time
)
FH
= sbioensembleplot(simdataObj
, Names
)
FH
= sbioensembleplot(simdataObj
, Names
, Time
)
| An object that contains simulation data. You can generate a object
using the function sbioensemblerun . All elements
of must contain
data for the same states in the same model. |
| Character vector, string, string vector, string array, or cell array of character vectors.
may include qualified names such as
'
or
'
to resolve ambiguities. Specifying {} or
empty string array (string.empty ) for
plots data for all states contained in
. |
| A numeric scalar value. If the specified is
not an element of the time vectors in ,
then the function resamples as
necessary using linear interpolation. |
| Array of handles to figure windows. |
sbioensembleplot(
shows
a 3-D shaded plot of time-varying distribution of all logged states
in the SimData array simdataObj
)
.
The simdataObj
sbioensemblerun
function plots an approximate
distribution created by fitting a normal distribution to the data
at every time step.
sbioensembleplot(
plots
the distribution for the data specified by simdataObj
, Names
)
.Names
sbioensembleplot(
plots
a 2-D histogram of the actual data of the ensemble distribution of
the states specified by simdataObj
, Names
, Time
)
at
the particular time point Names
.Time
returns
an array of handles FH
= sbioensembleplot(simdataObj
, Names
)
,
to the figure window for the 3-D distribution plot.FH
returns
an array of handles FH
= sbioensembleplot(simdataObj
, Names
, Time
)
,
to the figure window for the 2-D histograms.FH
This example shows how to plot data from an ensemble run without interpolation.
The project file, radiodecay.sbproj
,
contains a model stored in a variable called m1
.
Load m1
into the MATLAB® workspace.
sbioloadproject('radiodecay.sbproj','m1');
Change the solver of the active configuration set
to be ssa
. Also, adjust the LogDecimation
property
on the SolverOptions
property of the configuration
set to reduce the size of the data generated.
cs = getconfigset(m1, 'active'); set(cs, 'SolverType', 'ssa'); so = get(cs, 'SolverOptions'); set(so, 'LogDecimation', 10);
Perform an ensemble of 20 runs with no interpolation.
simdataObj = sbioensemblerun(m1, 20);
Create a 2-D distribution plot of the species 'z'
at
time = 1.0.
FH1 = sbioensembleplot(simdataObj, 'z', 1.0);
Create a 3-D shaded plot of both species.
FH2 = sbioensembleplot(simdataObj, {'x','z'});