Documentation

sbioensembleplot

Show results of ensemble run using 2-D or 3-D plots

Syntax

sbioensembleplot(simdataObj)
sbioensembleplot(simdataObj, Names)
sbioensembleplot(simdataObj, Names, Time)

FH = sbioensembleplot(simdataObj, Names)
FH = sbioensembleplot(simdataObj, Names, Time)

Arguments

simdataObjAn object that contains simulation data. You can generate a simdataObj object using the function sbioensemblerun. All elements of simdataObj must contain data for the same states in the same model.
NamesEither a string or a cell array of strings. Names may include qualified names such as 'CompartmentName.SpeciesName' or 'ReactionName.ParameterName' to resolve ambiguities. Specifying {} for Names plots data for all states contained in simdataObj.
TimeA numeric scalar value. If the specified Time is not an element of the time vectors in simdataObj, then the function resamples simdataObj as necessary using linear interpolation.
FHArray of handles to figure windows.

Description

sbioensembleplot(simdataObj) shows a 3-D shaded plot of time-varying distribution of all logged states in the SimData array simdataObj. The sbioensemblerun function plots an approximate distribution created by fitting a normal distribution to the data at every time step.

sbioensembleplot(simdataObj, Names) plots the distribution for the data specified by Names.

sbioensembleplot(simdataObj, Names, Time) plots a 2-D histogram of the actual data of the ensemble distribution of the states specified by Names at the particular time point Time.


FH = sbioensembleplot(simdataObj, Names)
returns an array of handles FH, to the figure window for the 3-D distribution plot.

FH = sbioensembleplot(simdataObj, Names, Time) returns an array of handles FH, to the figure window for the 2-D histograms.

Examples

This example shows how to plot data from an ensemble run without interpolation.

  1. The project file, radiodecay.sbproj, contains a model stored in a variable called m1. Load m1 into the MATLAB® workspace.

    sbioloadproject('radiodecay.sbproj','m1');
  2. 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);
  3. Perform an ensemble of 20 runs with no interpolation.

    simdataObj = sbioensemblerun(m1, 20);
  4. Create a 2-D distribution plot of the species 'z' at time = 1.0.

    FH1 = sbioensembleplot(simdataObj, 'z', 1.0);
  5. Create a 3-D shaded plot of both species.

    FH2 = sbioensembleplot(simdataObj, {'x','z'});
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